title
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string | arxiv_id
string | date
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1-OGC: The first open gravitational-wave catalog of binary mergers from analysis of public Advanced LIGO data
|
We present the first Open Gravitational-wave Catalog (1-OGC), obtained by
using the public data from Advanced LIGO's first observing run to search for
compact-object binary mergers. Our analysis is based on new methods that
improve the separation between signals and noise in matched-filter searches for
gravitational waves from the merger of compact objects. The three most
significant signals in our catalog correspond to the binary black hole mergers
GW150914, GW151226, and LVT151012. We observe these signals at a true discovery
rate of $99.92\%$. We find that LVT151012 alone has a 97.6$\%$ probability of
being astrophysical in origin. No other significant binary black hole
candidates are found, nor did we observe any significant binary neutron star or
neutron star--black hole candidates. We make available our complete catalog of
events, including the sub-threshold population of candidates.
|
http://arxiv.org/abs/1811.01921v2
|
1811.01921
|
2018-11-05
|
cybersecurity
|
1 {\Omega}-10 k{\Omega} high precision transportable setup to calibrate multifunction electrical instruments
|
A temperature controlled 1 {\Omega}-10 k{\Omega} standard Resistors
transportable setup was developed at National Institute of Metrological
Research, (INRIM) for the calibration and adjustment of multifunction
electrical instruments. The two Standards consist respectively of two 10
{\Omega} and 100 k{\Omega} parallel connected resistors nets inserted in a
temperature controlled aluminium box. Novelty of the realization is the oil
insertion of the 1 {\Omega} net with its internal connectors lowering the
thermo-electromotive forces (emfs) effects. Short and mid-term stabilities of
the setup Standards resulted on the order and in some cases better than other
top level 1 {\Omega} and 10 k{\Omega} commercial Standards. The transport
effect turning off the setup temperature control did not cause appreciable
measurement deviations on the two Standards. The Standards uncertainties meet
those requested by DMMs and MFCs manufacturers to calibrate and adjust these
instruments. A test to adjust a multifunction calibrator gave satisfactory
results.
|
http://arxiv.org/abs/1505.04398v1
|
1505.04398
|
2015-05-17
|
cybersecurity
|
1-out-of-2 Oblivious transfer using flawed Bit-string quantum protocol
|
Oblivious transfer (OT) is an important tool in cryptography. It serves as a
subroutine to other complex procedures of both theoretical and practical
significance. Common attribute of OT protocols is that one party (Alice) has to
send a message to another party (Bob) and has to stay oblivious on whether Bob
did receive the message. Specific (OT) protocols vary by exact definition of
the task - in the all-or-nothing protocol Alice sends a single bit-string
message, which Bob is able to read only with 50% probability, whereas in
1-out-of-2 OT protocol Bob reads one out of two messages sent by Alice. These
two flavours of protocol are known to be equivalent. Recently a computationally
secure all-or-nothing OT protocol based on quantum states was developed in [A.
Souto et. al., PRA 91, 042306], which however cannot be reduced to 1-out-of-2
OT protocol by standard means. Here we present an elaborated reduction of this
protocol which retains the security of the original.
|
http://arxiv.org/abs/1611.10087v1
|
1611.10087
|
2016-11-30
|
cybersecurity
|
1-out-of-n Oblivious Signatures: Security Revisited and a Generic Construction with an Efficient Communication Cost
|
1-out-of-n oblivious signature by Chen (ESORIC 1994) is a protocol between the user and the signer. In this scheme, the user makes a list of n messages and chooses the message that the user wants to obtain a signature from the list. The user interacts with the signer by providing this message list and obtains the signature for only the chosen message without letting the signer identify which messages the user chooses. Tso et al. (ISPEC 2008) presented a formal treatment of 1-out-of-n oblivious signatures. They defined unforgeability and ambiguity for 1-out-of-n oblivious signatures as a security requirement. In this work, first, we revisit the unforgeability security definition by Tso et al. and point out that their security definition has problems. We address these problems by modifying their security model and redefining unforgeable security. Second, we improve the generic construction of a 1-out-of-n oblivious signature scheme by Zhou et al. (IEICE Trans 2022). We reduce the communication cost by modifying their scheme with a Merkle tree. Then we prove the security of our modified scheme.
|
https://arxiv.org/abs/2404.00602v1
|
2404.00602
|
2024-03-31
|
cybersecurity
|
1-PAGER: One Pass Answer Generation and Evidence Retrieval
|
We present 1-Pager the first system that answers a question and retrieves evidence using a single Transformer-based model and decoding process. 1-Pager incrementally partitions the retrieval corpus using constrained decoding to select a document and answer string, and we show that this is competitive with comparable retrieve-and-read alternatives according to both retrieval and answer accuracy metrics. 1-Pager also outperforms the equivalent closed-book question answering model, by grounding predictions in an evidence corpus. While 1-Pager is not yet on-par with more expensive systems that read many more documents before generating an answer, we argue that it provides an important step toward attributed generation by folding retrieval into the sequence-to-sequence paradigm that is currently dominant in NLP. We also show that the search paths used to partition the corpus are easy to read and understand, paving a way forward for interpretable neural retrieval.
|
https://arxiv.org/abs/2310.16568v1
|
2310.16568
|
2023-10-25
|
cybersecurity
|
1 Particle - 1 Qubit: Particle Physics Data Encoding for Quantum Machine Learning
|
We introduce 1P1Q, a novel quantum data encoding scheme for high-energy physics (HEP), where each particle is assigned to an individual qubit, enabling direct representation of collision events without classical compression. We demonstrate the effectiveness of 1P1Q in quantum machine learning (QML) through two applications: a Quantum Autoencoder (QAE) for unsupervised anomaly detection and a Variational Quantum Circuit (VQC) for supervised classification of top quark jets. Our results show that the QAE successfully distinguishes signal jets from background QCD jets, achieving superior performance compared to a classical autoencoder while utilizing significantly fewer trainable parameters. Similarly, the VQC achieves competitive classification performance, approaching state-of-the-art classical models despite its minimal computational complexity. Furthermore, we validate the QAE on real experimental data from the CMS detector, establishing the robustness of quantum algorithms in practical HEP applications. These results demonstrate that 1P1Q provides an effective and scalable quantum encoding strategy, offering new opportunities for applying quantum computing algorithms in collider data analysis.
|
https://arxiv.org/abs/2502.17301v1
|
2502.17301
|
2025-02-24
|
cybersecurity
|
1-perfectly orientable graphs and graph products
|
A graph G is said to be 1-perfectly orientable (1-p.o. for short) if it
admits an orientation such that the out-neighborhood of every vertex is a
clique in G. The class of 1-p.o. graphs forms a common generalization of the
classes of chordal and circular arc graphs. Even though 1-p.o. graphs can be
recognized in polynomial time, no structural characterization of 1-p.o. graphs
is known. In this paper we consider the four standard graph products: the
Cartesian product, the strong product, the direct product, and the
lexicographic product. For each of them, we characterize when a nontrivial
product of two graphs is 1-p.o.
|
http://arxiv.org/abs/1511.07314v2
|
1511.07314
|
2016-08-30
|
cybersecurity
|
$1$-perfectly orientable $K_4$-minor-free and outerplanar graphs
|
A graph $G$ is said to be $1$-perfectly orientable if it has an orientation
such that for every vertex $v\in V(G)$, the out-neighborhood of $v$ in $D$ is a
clique in $G$. In $1982$, Skrien posed the problem of characterizing the class
of $1$-perfectly orientable graphs. This graph class forms a common
generalization of the classes of chordal and circular arc graphs; however,
while polynomially recognizable via a reduction to $2$-SAT, no structural
characterization of this intriguing class of graphs is known. Based on a
reduction of the study of $1$-perfectly orientable graphs to the biconnected
case, we characterize, both in terms of forbidden induced minors and in terms
of composition theorems, the classes of $1$-perfectly orientable
$K_4$-minor-free graphs and of $1$-perfectly orientable outerplanar graphs. As
part of our approach, we introduce a class of graphs defined similarly as the
class of $2$-trees and relate the classes of graphs under consideration to two
other graph classes closed under induced minors studied in the literature:
cyclically orientable graphs and graphs of separability at most~$2$.
|
http://arxiv.org/abs/1604.04598v2
|
1604.04598
|
2016-04-19
|
cybersecurity
|
1-planar graphs are odd 13-colorable
|
An odd coloring of a graph $G$ is a proper coloring such that any non-isolated vertex in $G$ has a coloring appears odd times on its neighbors. The odd chromatic number, denoted by $\chi_o(G)$, is the minimum number of colors that admits an odd coloring of $G$. Petru\v{s}evski and \v{S}krekovski in 2021 introduced this notion and proved that if $G$ is planar, then $\chi_o(G)\le9$ and conjectured that $\chi_o(G)\le5$. More recently, Petr and Portier improved $9$ to $8$. A graph is $1$-planar if it can be drawn in the plane so that each edge is crossed by at most one other edge. Cranston, Lafferty and Song showed that every $1$-planar graph is odd $23$-colorable. In this paper, we improved this result and showed that every $1$-planar graph is odd $13$-colorable.
|
https://arxiv.org/abs/2206.13967v1
|
2206.13967
|
2022-06-28
|
cybersecurity
|
1-planar graphs with minimum degree at least 3 have bounded girth
|
We show that every 1-planar graph with minimum degree at least 4 has girth at
most $8$, and every 1-planar graph with minimum degree at least 3 has girth at
most $198$.
|
http://arxiv.org/abs/2001.05402v2
|
2001.05402
|
2020-01-16
|
cybersecurity
|
1-planar unit distance graphs
|
A matchstick graph is a plane graph with edges drawn as unit distance line segments. This class of graphs was introduced by Harborth who conjectured that a matchstick graph on $n$ vertices can have at most $\lfloor 3n - \sqrt{12n - 3}\rfloor$ edges. Recently his conjecture was settled by Lavoll\'ee and Swanepoel. In this paper we consider $1$-planar unit distance graphs. We say that a graph is a $1$-planar unit distance graph if it can be drawn in the plane such that all edges are drawn as unit distance line segments while each of them are involved in at most one crossing. We show that such graphs on $n$ vertices can have at most $3n-\sqrt[4]{n}/10$ edges.
|
https://arxiv.org/abs/2310.00940v1
|
2310.00940
|
2023-10-02
|
cybersecurity
|
1PN effective binary Lagrangian for the gravity-Kalb-Ramond sector in the conservative regime
|
Within the framework of string theory, a number of new fields are possible correcting the Einstein-Hilbert action, including a Kalb-Ramond two-form field. In this work we derive explicitly first order relativistic corrections to conservative dynamics with a Kalb-Ramond field, using the effective field theory approach. The resulting additional terms in the Lagrangian governing conservative binary dynamics are presented explicitly.
|
https://arxiv.org/abs/2312.11322v1
|
2312.11322
|
2023-12-18
|
cybersecurity
|
1-Point Functions for $\mathbb{Z}_2$-orbifolds of Lattice VOAs
|
In this paper, we compute the 1-point correlation functions of all states for the $\mathbb{Z}_2$-orbifolds of lattice vertex operator algebras.
|
https://arxiv.org/abs/2505.02954v1
|
2505.02954
|
2025-05-05
|
cybersecurity
|
1-point functions for symmetrized Heisenberg and symmetrized lattice vertex operator algebras
|
We obtain explicit formulas for the $1$-point functions of all states in the symmetrized Heisenberg algebra $M^+$ and symmetrized lattice VOAs $V_L^+$. For this we employ a new $\mathbf Z_2$-twisted variant of so-called Zhu recursion.
|
https://arxiv.org/abs/2204.08318v1
|
2204.08318
|
2022-04-18
|
cybersecurity
|
1-Point RANSAC-Based Method for Ground Object Pose Estimation
|
Solving Perspective-n-Point (PnP) problems is a traditional way of estimating object poses. Given outlier-contaminated data, a pose of an object is calculated with PnP algorithms of n = {3, 4} in the RANSAC-based scheme. However, the computational complexity considerably increases along with n and the high complexity imposes a severe strain on devices which should estimate multiple object poses in real time. In this paper, we propose an efficient method based on 1-point RANSAC for estimating a pose of an object on the ground. In the proposed method, a pose is calculated with 1-DoF parameterization by using a ground object assumption and a 2D object bounding box as an additional observation, thereby achieving the fastest performance among the RANSAC-based methods. In addition, since the method suffers from the errors of the additional information, we propose a hierarchical robust estimation method for polishing a rough pose estimate and discovering more inliers in a coarse-to-fine manner. The experiments in synthetic and real-world datasets demonstrate the superiority of the proposed method.
|
https://arxiv.org/abs/2008.03718v2
|
2008.03718
|
2020-08-09
|
cybersecurity
|
1-point RANSAC for Circular Motion Estimation in Computed Tomography (CT)
|
This paper proposes a RANSAC-based algorithm for determining the axial rotation angle of an object from a pair of its tomographic projections. An equation is derived for calculating the rotation angle using one correct keypoints correspondence of two tomographic projections. The proposed algorithm consists of the following steps: keypoints detection and matching, rotation angle estimation for each correspondence, outliers filtering with the RANSAC algorithm, finally, calculation of the desired angle by minimizing the re-projection error from the remaining correspondences. To validate the proposed method an experimental comparison against methods based on analysis of the distribution of the angles computed from all correspondences is conducted.
|
https://arxiv.org/abs/1910.01681v1
|
1910.01681
|
2019-10-03
|
cybersecurity
|
$1$-product problems with congruence conditions in nonabelian groups
|
Let $G$ be a finite group and $D_{2n}$ be the dihedral group of $2n$
elements. For a positive integer $d$, let $\mathsf{s}_{d\mathbb{N}}(G)$ denote
the smallest integer $\ell\in \mathbb{N}_0\cup \{+\infty\}$ such that every
sequence $S$ over $G$ of length $|S|\geq \ell$ has a nonempty $1$-product
subsequence $T$ with $|T|\equiv 0$ (mod $d$). In this paper, we mainly study
the problem for dihedral groups $D_{2n}$ and determine their exact values:
$\mathsf{s}_{d\mathbb{N}}(D_{2n})=2d+\lfloor log_2n\rfloor$, if $d$ is odd with
$n|d$; $\mathsf{s}_{d\mathbb{N}}(D_{2n})=nd+1$, if $gcd(n,d)=1$. Furthermore,
we also analysis the problem for metacyclic groups $C_p\ltimes_s C_q$ and
obtain a result: $\mathsf{s}_{kp\mathbb{N}}(C_p\ltimes_s
C_q)=lcm(kp,q)+p-2+gcd(kp,q)$, where $p\geq 3$ and $p|q-1$.
|
http://arxiv.org/abs/2003.14007v1
|
2003.14007
|
2020-03-31
|
cybersecurity
|
(1,p)-Sobolev spaces based on strongly local Dirichlet forms
|
In the framework of quasi-regular strongly local Dirichlet form $(\mathscr{E},D(\mathscr{E}))$ on $L^2(X;\mathfrak{m})$ admitting minimal $\mathscr{E}$-dominant measure $\mu$, we construct a natural $p$-energy functional $(\mathscr{E}^{\,p},D(\mathscr{E}^{\,p}))$ on $L^p(X;\mathfrak{m})$ and $(1,p)$-Sobolev space $(H^{1,p}(X),\|\cdot\|_{H^{1,p}})$ for $p\in]1,+\infty[$. In this paper, we establish the Clarkson type inequality for $(H^{1,p}(X),\|\cdot\|_{H^{1,p}})$. As a consequence, $(H^{1,p}(X),\|\cdot\|_{H^{1,p}})$ is a uniformly convex Banach space, hence it is reflexive. Based on the reflexivity of $(H^{1,p}(X),\|\cdot\|_{H^{1,p}})$, we prove that (generalized) normal contraction operates on $(\mathscr{E}^{\,p},D(\mathscr{E}^{\,p}))$, which has been shown in the case of various concrete settings, but has not been proved for such general framework. Moreover, we prove that $(1,p)$-capacity ${\rm Cap}_{1,p}(A)<\infty$ for open set $A$ admits an equilibrium potential $e_A\in D(\mathscr{E}^{\,p})$ with $0\leq e_A\leq 1$ $\mathfrak{m}$-a.e. and $e_A=1$ $\mathfrak{m})$-a.e.~on $A$.
|
https://arxiv.org/abs/2310.11652v2
|
2310.11652
|
2023-10-18
|
cybersecurity
|
$1/Q^2$ power corrections to TMD factorization for Drell-Yan hadronic tensor
|
I calculate ${1\over Q^2}$ power corrections to unpolarized Drell-Yan hadronic tensor for electromagnetic (EM) current at large $N_c$ and demonstrate the EM gauge invariance at this level.
|
https://arxiv.org/abs/2404.15116v3
|
2404.15116
|
2024-04-23
|
cybersecurity
|
1RXH J082623.6-505741: a new long-period cataclysmic variable with an evolved donor and a low mass transfer rate
|
We report the discovery of 1RXH J082623.6-505741, a 10.4 hr orbital period compact binary. Modeling extensive optical photometry and spectroscopy reveals a $\sim 0.4 M_{\odot}$ K-type secondary transferring mass through a low-state accretion disk to a non-magnetic $\sim 0.8 M_{\odot}$ white dwarf. The secondary is overluminous for its mass and dominates the optical spectra at all epochs, and must be evolved to fill its Roche Lobe at this orbital period. The X-ray luminosity $L_X \sim 1$-$2 \times 10^{32}$ erg s$^{-1}$ derived from both new XMM-Newton and archival observations, although high compared to most CVs, still only requires a modest accretion rate onto the white dwarf of $\dot{M} \sim 3 \times 10^{-11}$ to $3 \times 10^{-10} M_{\odot}$ yr$^{-1}$, lower than expected for a cataclysmic variable with an evolved secondary. No dwarf nova outbursts have yet been observed from the system, consistent with the low derived mass transfer rate. Several other cataclysmic variables with similar orbital periods also show unexpectedly low mass transfer rates, even though selection effects disfavor the discovery of binaries with these properties. This suggests the abundance and evolutionary state of long-period, low mass transfer rate cataclysmic variables is worthy of additional attention.
|
https://arxiv.org/abs/2206.10625v1
|
2206.10625
|
2022-06-21
|
cybersecurity
|
1RXS J161935.7+524630: New Polar with the Varying Accretion Modes on two Magnetic Poles
|
We report the discovery of a new cataclysmic variable DDE 32 identified with
the ROSAT X-ray source 1RXS J161935.7+524630 in Draco. The variability was
originally found by D. Denisenko on the digitized Palomar plates centered at
the position of X-ray source. The photometric observations by F. Martinelli at
Lajatico Astronomical Center in June 2015 have shown the large amplitude
(nearly 2 magnitudes) variability with a period about 100.5 minutes. Using the
publicly available Catalina Sky Survey data from 2005 to 2013 we have improved
the value of period to 0.0697944 days. Comparison of the archival CRTS data
with more recent observations from Lajatico shows the dramatic changes in the
light curve shape. Instead of a single peak present in Catalina data before
2014, there were two peaks of nearly the same height during 2015. SDSS spectrum
taken in June 2009 shows prominent Helium emission lines between the bright
Balmer series. He II 4686 AA line has more than 30% effective width compared to
H_beta line. All those features allow us to interpret 1RXS J161935.7+524630 as
a magnetic cataclysmic variable (polar) with the accretion mode changing from
one pole before 2014 to two poles in 2015.
|
http://arxiv.org/abs/1609.08511v1
|
1609.08511
|
2016-09-27
|
cybersecurity
|
1RXS J180408.9-342058: an ultra compact X-ray binary candidate with a transient jet
|
We present a detailed NIR/optical/UV study of the transient low mass X-ray
binary 1RXS J180408.9-342058 performed during its 2015 outburst, aimed at
determining the nature of its companion star. We obtained three optical spectra
at the 2.1 m San Pedro Martir Observatory telescope (Mexico). We performed
optical and NIR photometric observations with both the REM telescope and the
New Technology Telescope (NTT) in La Silla. We obtained optical and UV
observations from the Swift archive. Finally, we performed optical polarimetry
of the source by using the EFOSC2 instrument mounted on the NTT. The optical
spectrum of the source is almost featureless since the hydrogen and He I
emissions lines, typically observed in LMXBs, are not detected. Similarly,
carbon and oxygen lines are neither observed. We marginally detect the He II
4686 AA emission line, suggesting the presence of helium in the accretion disc.
No significant optical polarisation level was observed. The lack of hydrogen
and He I emission lines in the spectrum implies that the companion is likely
not a main sequence star. Driven by the tentative detection of the He II 4686
AA emission line, we suggest that the system could harbour a helium white
dwarf. If this is the case, 1RXS J180408.9-342058 would be an ultra-compact
X-ray binary. By combining an estimate of the mass accretion rate together with
evolutionary tracks for a He white dwarf, we obtain a tentative orbital period
of ~ 40 min. On the other hand, we also built the NIR-optical-UV spectral
energy distribution (SED) of the source at two different epochs. One SED was
gathered when the source was in the soft X-ray state, and it is consistent with
the presence of a single thermal component. The second SED, obtained when the
source was in the hard X-ray state, shows a thermal component together with a
tail in the NIR, likely indicating the presence of a (transient) jet.
|
http://arxiv.org/abs/1601.05091v1
|
1601.05091
|
2016-01-19
|
cybersecurity
|
$^1S_0$ pairing for neutrons in dense neutron matter induced by a soft pion
|
The possibility of neutron pairing in the $^1S_0$ channel is studied for
dense neutron matter in a vicinity of the $\pi^0$ condensation point. The
$^1S_0$ pairing gap $\Delta$ is shown to occur in a model with a pairing force
induced by the exchange of a soft neutral pionic mode. The soft pion induced
potential $V_{\pi}(r)$ is characterized by an attenuating oscillatory behavior
in coordinate space, while in momentum space all $S$-wave matrix elements
$V_{\pi}(p,p')$ are positive. The solution of the gap equation reveals strong
momentum dependence.
|
http://arxiv.org/abs/1409.7225v2
|
1409.7225
|
2015-01-19
|
cybersecurity
|
$^1$S$_0$ pairing gaps, chemical potential and entrainment matrix in superfluid neutron-star cores for the Brussels-Montreal functionals
|
Temperature and velocity-dependent $^1$S$_0$ pairing gaps, chemical potentials and entrainment matrix in dense homogeneous neutron-proton superfluid mixtures constituting the outer core of neutron stars, are determined fully self-consistently by solving numerically the time-dependent Hartree-Fock-Bogoliubov equations over the whole range of temperatures and flow velocities for which superfluidity can exist. Calculations have been made for $npe\mu$ in beta-equilibrium using the Brussels-Montreal functional BSk24. The accuracy of various approximations is assessed and the physical meaning of the different velocities and momentum densities appearing in the theory is clarified. Together with the unified equation of state published earlier, the present results provide consistent microscopic inputs for modeling superfluid neutron-star cores.
|
https://arxiv.org/abs/2203.08778v1
|
2203.08778
|
2022-03-16
|
cybersecurity
|
$^1S_0$ pairing in neutron matter
|
We report calculations of the superfluid pairing gap in neutron matter for
the $^1S_0$ components of the Reid soft-core $V_6$ and the Argonne $V_{4}'$
two-nucleon interactions. Ground-state calculations have been carried out using
the central part of the operator-basis representation of these interactions to
determine optimal Jastrow-Feenberg correlations and corresponding effective
pairing interactions within the correlated-basis formalism (CBF), the required
matrix elements in the correlated basis being evaluated by Fermi
hypernetted-chain techniques. Different implementations of the
Fermi-Hypernetted Chain Euler-Lagrange method (FHNC-EL) agree at the percent
level up to nuclear matter saturation density. For the assumed interactions,
which are realistic within the low density range involved in $^1S_0$ neutron
pairing, we did not find a dimerization instability arising from divergence of
the in-medium scattering length, as was reported recently for simple
square-well and Lennard-Jones potential models (Phys. Rev. A {\bf 92}, 023640
(2015)).
|
http://arxiv.org/abs/1707.07268v1
|
1707.07268
|
2017-07-23
|
cybersecurity
|
1S-3S cw spectroscopy of hydrogen/deuterium atom
|
We study the 1S-3S two-photon transition of hydrogen in a thermal atomic beam, using a homemade cw laser source at 205 nm. The experimental method is described, leading in 2017 to the measurement of the 1S-3S transition frequency in hydrogen atom with a relative uncertainty of $9 \times 10^{-13}$. This result contributes to the "proton puzzle" resolution but is in disagreement with the ones of some others experiments. We have recently improved our setup with the aim of carrying out the same measurement in deuterium. With the improved detection system, we have observed a broadened fluorescence signal, superimposed on the narrow signal studied so far, and due to the stray accumulation of atoms in the vacuum chamber. The possible resulting systematic effect is discussed.
|
https://arxiv.org/abs/2302.07537v1
|
2302.07537
|
2023-02-15
|
cybersecurity
|
1-Safe Petri nets and special cube complexes: equivalence and applications
|
Nielsen, Plotkin, and Winskel (1981) proved that every 1-safe Petri net $N$
unfolds into an event structure $\mathcal{E}_N$. By a result of Thiagarajan
(1996 and 2002), these unfoldings are exactly the trace regular event
structures. Thiagarajan (1996 and 2002) conjectured that regular event
structures correspond exactly to trace regular event structures. In a recent
paper (Chalopin and Chepoi, 2017, 2018), we disproved this conjecture, based on
the striking bijection between domains of event structures, median graphs, and
CAT(0) cube complexes. On the other hand, in Chalopin and Chepoi (2018) we
proved that Thiagarajan's conjecture is true for regular event structures whose
domains are principal filters of universal covers of (virtually) finite special
cube complexes.
In the current paper, we prove the converse: to any finite 1-safe Petri net
$N$ one can associate a finite special cube complex ${X}_N$ such that the
domain of the event structure $\mathcal{E}_N$ (obtained as the unfolding of
$N$) is a principal filter of the universal cover $\widetilde{X}_N$ of $X_N$.
This establishes a bijection between 1-safe Petri nets and finite special cube
complexes and provides a combinatorial characterization of trace regular event
structures.
Using this bijection and techniques from graph theory and geometry (MSO
theory of graphs, bounded treewidth, and bounded hyperbolicity) we disprove yet
another conjecture by Thiagarajan (from the paper with S. Yang from 2014) that
the monadic second order logic of a 1-safe Petri net is decidable if and only
if its unfolding is grid-free.
Our counterexample is the trace regular event structure $\mathcal{\dot E}_Z$
which arises from a virtually special square complex $\dot Z$. The domain of
$\mathcal{\dot E}_Z$ is grid-free (because it is hyperbolic), but the MSO
theory of the event structure $\mathcal{\dot E}_Z$ is undecidable.
|
http://arxiv.org/abs/1810.03395v2
|
1810.03395
|
2019-04-24
|
cybersecurity
|
1-Shell totally symmetric plane partitions (TSPPs) modulo powers of 5
|
Let $s(n)$ be the number of 1-shell totally symmetric plane partitions
(TSPPs) of $n$. In this paper, an infinite family of congruences modulo powers
of $5$ for $s(n)$ will be deduced through an elementary approach. Namely,
$$s\left(2\cdot 5^{2\alpha-1}n+5^{2\alpha-1}\right)\equiv 0
\pmod{5^{\alpha}}.$$
|
http://arxiv.org/abs/1802.04344v2
|
1802.04344
|
2020-03-26
|
cybersecurity
|
1-shifted Lie bialgebras and their quantizations
|
In this paper, we define (cohomologically) 1-shifted Manin triples and 1-shifted Lie bialgebras, and study their properties. We derive many results that are parallel to those found in ordinary Lie bialgebras, including the double construction and the existence of a 1-shifted $r$-matrix satisfying the classical Yang-Baxter equation. Turning to quantization, we first construct a canonical quantization for each 1-shifted metric Lie algebra $\mathfrak{g}$, producing a deformation to the symmetric monoidal category of $\mathfrak{g}$ modules over a formal variable $\hbar$. This quantization is in terms of a curved differential graded algebra. Under a further technical assumption, we construct quantizations of transverse Lagrangian subalgebras of $\mathfrak{g}$, which is a pair of DG algebras connected by Koszul duality, and give rise to monoidal module categories of the quantized double. Finally, we apply this to Manin triples arising from Lie algebras of loop groups, and construct 1-shifted meromorphic $r$-matrices. The resulting quantizations are the cohomologically-shifted analogue of Yangians.
|
https://arxiv.org/abs/2503.08770v1
|
2503.08770
|
2025-03-11
|
cybersecurity
|
1-Shot Oblivious Transfer and 2-Party Computation from Noisy Quantum Storage
|
Few primitives are as intertwined with the foundations of cryptography as Oblivious Transfer (OT). Not surprisingly, with the advent of the use of quantum resources in information processing, OT played a central role in establishing new possibilities (and defining impossibilities) pertaining to the use of these novel assets. A major research path is minimizing the required assumptions to achieve OT, and studying their consequences. Regarding its computation, it is impossible to construct unconditionally-secure OT without extra assumptions; and, regarding communication complexity, achieving 1-shot (and even non-interactive) OT has proved to be an elusive task, widely known to be impossible classically. Moreover, this has strong consequencesfor realizing round-optimal secure computation, in particular 1-shot 2-Party Computation (2PC). In this work, three main contributions are evidenced by leveraging quantum resources: 1. Unconditionally-secure 2-message non-interactive OT protocol constructed in the Noisy-Quantum-Storage Model. 2. 1-shot OT in the Noisy-Quantum-Storage Model -- proving that this construction is possible assuming the existence of one-way functions and sequential functions. 3. 1-shot 2PC protocol compiled from a semi-honest 1-shot OT to semi-honest 1-shot Yao's Garbled Circuits protocol.
|
https://arxiv.org/abs/2410.08367v1
|
2410.08367
|
2024-10-10
|
cybersecurity
|
1-skeletons of the spanning tree problems with additional constraints
|
We consider the polyhedral properties of two spanning tree problems with
additional constraints. In the first problem, it is required to find a tree
with a minimum sum of edge weights among all spanning trees with the number of
leaves less or equal a given value. In the second problem, an additional
constraint is the assumption that the degree of all vertices of the spanning
tree does not exceed a given value. The decision versions of both problems are
NP-complete.
We consider the polytopes of these problems and their 1-skeletons. We prove
that in both cases it is a NP-complete problem to determine whether the
vertices of 1-skeleton are adjacent. Although it is possible to obtain a
superpolynomial lower bounds on the clique numbers of these graphs. These
values characterize the time complexity in a broad class of algorithms based on
linear comparisons. The results indicate a fundamental difference in
combinatorial and geometric properties between the considered problems and the
classical minimum spanning tree problem.
|
http://arxiv.org/abs/1710.09672v1
|
1710.09672
|
2017-10-26
|
cybersecurity
|
1-smooth pro-p groups and Bloch-Kato pro-p groups
|
Let $p$ be a prime. A pro-$p$ group $G$ is said to be 1-smooth if it can be endowed with a homomorphism of pro-$p$ groups $G\to1+p\mathbb{Z}_p$ satisfying a formal version of Hilbert 90. By Kummer theory, maximal pro-$p$ Galois groups of fields containing a root of 1 of order $p$, together with the cyclotomic character, are 1-smooth. We prove that a finitely generated $p$-adic analytic pro-$p$ group is 1-smooth if, and only if, it occurs as the maximal pro-$p$ Galois group of a field containing a root of 1 of order $p$. This gives a positive answer to De Clerq-Florence's "Smoothness Conjecture" - which states that the Rost-Voevodsky Theorem (a.k.a. Bloch-Kato Conjecture) follows from 1-smoothness - for the class of finitely generated $p$-adic analytic pro-$p$ groups.
|
https://arxiv.org/abs/1904.00667v7
|
1904.00667
|
2019-04-01
|
cybersecurity
|
1SPU: 1-step Speech Processing Unit
|
Recent studies have made some progress in refining end-to-end (E2E) speech recognition encoders by applying Connectionist Temporal Classification (CTC) loss to enhance named entity recognition within transcriptions. However, these methods have been constrained by their exclusive use of the ASCII character set, allowing only a limited array of semantic labels. We propose 1SPU, a 1-step Speech Processing Unit which can recognize speech events (e.g: speaker change) or an NL event (Intent, Emotion) while also transcribing vocal content. It extends the E2E automatic speech recognition (ASR) system's vocabulary by adding a set of unused placeholder symbols, conceptually akin to the <pad> tokens used in sequence modeling. These placeholders are then assigned to represent semantic events (in form of tags) and are integrated into the transcription process as distinct tokens. We demonstrate notable improvements on the SLUE benchmark and yields results that are on par with those for the SLURP dataset. Additionally, we provide a visual analysis of the system's proficiency in accurately pinpointing meaningful tokens over time, illustrating the enhancement in transcription quality through the utilization of supplementary semantic tags.
|
https://arxiv.org/abs/2311.04753v3
|
2311.04753
|
2023-11-08
|
cybersecurity
|
$1$-stable fluctuation of the derivative martingale of branching random walk
|
In this paper, we study the functional convergence in law of the fluctuations of the derivative martingale of branching random walk on the real line. Our main result strengthens the results of Buraczewski et. al. [Ann. Probab., 2021] and is the branching random walk counterpart of the main result of Maillard and Pain [Ann. Probab., 2019] for branching Brownian motion.
|
https://arxiv.org/abs/2311.16407v1
|
2311.16407
|
2023-11-28
|
cybersecurity
|
1-stable fluctuations in branching Brownian motion at critical temperature II: general functionals
|
Let $\mu_t$ denote the critical derivative Gibbs measure of branching Brownian motion at time $t$. It has been proved by Madaule [Stochastic Process. Appl., 126(2):470--502, 2016] and Maillard and Zeitouni [Ann. Inst. Henri Poincar\'e Probab. Stat., 52(3):1144--1160, 2016] that $\mu_t$ converges weakly to the random measure $Z_\infty \sqrt{2/\pi} x^2 e^{-x^2/2} \mathbb{1}_{x >0} \,\mathrm{d} x$, where $Z_\infty$ is the limit of the derivative martingale. In this paper, we are interested in the fluctuations that occur in this convergence and prove for a large class of functions $F$ that \[ \sqrt{t} \left( \int_{\mathbb{R}} F \,\mathrm{d} \mu_t - Z_\infty \int_0^\infty F(x) \sqrt{\frac{2}{\pi}} x^2 e^{-x^2/2} \,\mathrm{d} x - \frac{c(F) \log t}{\sqrt{t}} Z_\infty \right) \xrightarrow[t\to\infty]{} S^F_{Z_\infty}, \quad \text{in law}, \] where $c(F)$ is a constant depending on $F$ and $(S^F_r)_{r\geq0}$ is a 1-stable L\'evy process independent of $Z_\infty$. Moreover, we extend this result to a functional convergence, and we identify precisely the particles responsible for the fluctuations. In particular, this proves the following result for the critical additive martingale $(W_t)_{t\geq 0}$: \[ \sqrt{t} \left( \sqrt{t} W_t - \sqrt{\frac{2}{\pi}} Z_\infty \right) \xrightarrow[t\to\infty]{} S_{Z_\infty}, \quad \text{in law}, \] where here $(S_r)_{r\geq0}$ is a Cauchy process independent of $Z_\infty$, confirming a conjecture by Mueller and Munier [Phys. Rev. E, 90:042143, 2014] in the physics literature.
|
https://arxiv.org/abs/2103.10412v1
|
2103.10412
|
2021-03-18
|
cybersecurity
|
1-stable fluctuations in branching Brownian motion at critical temperature I: the derivative martingale
|
Let $(Z_t)_{t\geq 0}$ denote the derivative martingale of branching Brownian
motion, i.e.\@ the derivative with respect to the inverse temperature of the
normalized partition function at critical temperature. A well-known result by
Lalley and Sellke [\textit{Ann. Probab.}, 15(3):1052--1061, 1987] says that
this martingale converges almost surely to a limit $Z_\infty$, positive on the
event of survival. In this paper, our concern is the fluctuations of the
derivative martingale around its limit. A corollary of our results is the
following convergence, confirming and strengthening a conjecture by Mueller and
Munier [\textit{Phys. Rev. E}, 90:042143, 2014]: \[ \sqrt{t} \left( Z_\infty -
Z_t + \frac{\log t}{\sqrt{2\pi t}} Z_\infty \right) \xrightarrow[t\to\infty]{}
S_{Z_\infty}, \quad \text{in law}, \] where $S$ is a spectrally positive
1-stable L\'evy process independent of $Z_\infty$.
In a first part of the paper, a relatively short proof of (a slightly
stronger form of) this convergence is given based on the functional equation
satisfied by the characteristic function of $Z_\infty$ together with tail
asymptotics of this random variable. We then set up more elaborate arguments
which yield a more thorough understanding of the trajectories of the particles
contributing to the fluctuations. In this way, we can upgrade our convergence
result to functional convergence. This approach also sets the ground for a
follow-up paper, where we study the fluctuations of more general functionals
including the renormalized critical additive martingale.
All proofs in this paper are given under the hypothesis $E[L(\log L)^3] <
\infty$, where the random variable $L$ follows the offspring distribution of
the branching Brownian motion. We believe this hypothesis to be optimal.
|
http://arxiv.org/abs/1806.05152v2
|
1806.05152
|
2018-06-19
|
cybersecurity
|
1st AfricaNLP Workshop Proceedings, 2020
|
Proceedings of the 1st AfricaNLP Workshop held on 26th April alongside ICLR 2020, Virtual Conference, Formerly Addis Ababa Ethiopia.
|
https://arxiv.org/abs/2011.10361v1
|
2011.10361
|
2020-11-20
|
cybersecurity
|
1st eigenvalue pinching for convex hypersurfaces in a Riemannian manifold
|
Let $M^n$ be a closed convex hypersurface lying in a convex ball $B(p,R)$ of
the ambient $(n+1)$-manifold $N^{n+1}$. We prove that, by pinching
Heintze-Reilly's inequality via sectional curvature upper bound of $B(p,R)$,
1st eigenvalue and mean curvature of $M$, not only $M$ is Hausdorff close and
almost isometric to a geodesic sphere $S(p_0,R_0)$ in $N$, but also its
enclosed domain is $C^{1,\alpha}$-close to a geodesic ball of constant
curvature.
|
http://arxiv.org/abs/1905.05572v1
|
1905.05572
|
2019-05-14
|
cybersecurity
|
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct)
|
Recent years have seen advances on principles and guidance relating to accountable and ethical use of artificial intelligence (AI) spring up around the globe. Specifically, Data Privacy, Accountability, Interpretability, Robustness, and Reasoning have been broadly recognized as fundamental principles of using machine learning (ML) technologies on decision-critical and/or privacy-sensitive applications. On the other hand, in tremendous real-world applications, data itself can be well represented as various structured formalisms, such as graph-structured data (e.g., networks), grid-structured data (e.g., images), sequential data (e.g., text), etc. By exploiting the inherently structured knowledge, one can design plausible approaches to identify and use more relevant variables to make reliable decisions, thereby facilitating real-world deployments.
|
https://arxiv.org/abs/2210.03612v1
|
2210.03612
|
2022-10-07
|
cybersecurity
|
1st-Order Dynamics on Nonlinear Agents for Resource Allocation over Uniformly-Connected Networks
|
A general nonlinear $1$st-order consensus-based solution for distributed constrained convex optimization is proposed with network resource allocation applications. The solution is used to optimize continuously-differentiable strictly convex cost functions over weakly-connected undirected networks, while it is anytime feasible and models various nonlinearities to account for imperfections and constraints on the (physical model of) agents in terms of limited actuation capabilities, e.g., quantization and saturation. Due to such inherent nonlinearities, the existing linear solutions considering ideal agent models may not necessarily converge with guaranteed optimality and anytime feasibility. Some applications also impose specific nonlinearities, e.g., convergence in fixed/finite-time or sign-based robust disturbance-tolerant dynamics. Our proposed distributed protocol generalizes such nonlinear models. Putting convex set analysis together with nonsmooth Lyapunov analysis, we prove convergence, (i) regardless of the particular type of nonlinearity, and (ii) with weak network-connectivity requirements (uniform-connectivity).
|
https://arxiv.org/abs/2109.04822v2
|
2109.04822
|
2021-09-10
|
cybersecurity
|
1st-Order Magic: Analysis of Sharpness-Aware Minimization
|
Sharpness-Aware Minimization (SAM) is an optimization technique designed to improve generalization by favoring flatter loss minima. To achieve this, SAM optimizes a modified objective that penalizes sharpness, using computationally efficient approximations. Interestingly, we find that more precise approximations of the proposed SAM objective degrade generalization performance, suggesting that the generalization benefits of SAM are rooted in these approximations rather than in the original intended mechanism. This highlights a gap in our understanding of SAM's effectiveness and calls for further investigation into the role of approximations in optimization.
|
https://arxiv.org/abs/2411.01714v1
|
2411.01714
|
2024-11-03
|
cybersecurity
|
1st Place in ICCV 2023 Workshop Challenge Track 1 on Resource Efficient Deep Learning for Computer Vision: Budgeted Model Training Challenge
|
The budgeted model training challenge aims to train an efficient classification model under resource limitations. To tackle this task in ImageNet-100, we describe a simple yet effective resource-aware backbone search framework composed of profile and instantiation phases. In addition, we employ multi-resolution ensembles to boost inference accuracy on limited resources. The profile phase obeys time and memory constraints to determine the models' optimal batch-size, max epochs, and automatic mixed precision (AMP). And the instantiation phase trains models with the determined parameters from the profile phase. For improving intra-domain generalizations, the multi-resolution ensembles are formed by two-resolution images with randomly applied flips. We present a comprehensive analysis with expensive experiments. Based on our approach, we win first place in International Conference on Computer Vision (ICCV) 2023 Workshop Challenge Track 1 on Resource Efficient Deep Learning for Computer Vision (RCV).
|
https://arxiv.org/abs/2311.11470v1
|
2311.11470
|
2023-08-09
|
cybersecurity
|
1st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation
|
The recent transformer-based models have dominated the Referring Video Object Segmentation (RVOS) task due to the superior performance. Most prior works adopt unified DETR framework to generate segmentation masks in query-to-instance manner. In this work, we integrate strengths of that leading RVOS models to build up an effective paradigm. We first obtain binary mask sequences from the RVOS models. To improve the consistency and quality of masks, we propose Two-Stage Multi-Model Fusion strategy. Each stage rationally ensembles RVOS models based on framework design as well as training strategy, and leverages different video object segmentation (VOS) models to enhance mask coherence by object propagation mechanism. Our method achieves 75.7% J&F on Ref-Youtube-VOS validation set and 70% J&F on test set, which ranks 1st place on 5th Large-scale Video Object Segmentation Challenge (ICCV 2023) track 3. Code is available at https://github.com/RobertLuo1/iccv2023_RVOS_Challenge.
|
https://arxiv.org/abs/2401.00663v1
|
2401.00663
|
2024-01-01
|
cybersecurity
|
1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020
|
This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly based on Actor-Context-Actor Relation Network. We describe technical details for the new AVA-Kinetics dataset, together with some experimental results. Without any bells and whistles, we achieved 39.62 mAP on the test set of AVA-Kinetics, which outperforms other entries by a large margin. Code will be available at: https://github.com/Siyu-C/ACAR-Net.
|
https://arxiv.org/abs/2006.09116v1
|
2006.09116
|
2020-06-16
|
cybersecurity
|
1st Place Solution for CVPR2023 BURST Long Tail and Open World Challenges
|
Currently, Video Instance Segmentation (VIS) aims at segmenting and categorizing objects in videos from a closed set of training categories that contain only a few dozen of categories, lacking the ability to handle diverse objects in real-world videos. As TAO and BURST datasets release, we have the opportunity to research VIS in long-tailed and open-world scenarios. Traditional VIS methods are evaluated on benchmarks limited to a small number of common classes, But practical applications require trackers that go beyond these common classes, detecting and tracking rare and even never-before-seen objects. Inspired by the latest MOT paper for the long tail task (Tracking Every Thing in the Wild, Siyuan Li et), for the BURST long tail challenge, we train our model on a combination of LVISv0.5 and the COCO dataset using repeat factor sampling. First, train the detector with segmentation and CEM on LVISv0.5 + COCO dataset. And then, train the instance appearance similarity head on the TAO dataset. at last, our method (LeTracker) gets 14.9 HOTAall in the BURST test set, ranking 1st in the benchmark. for the open-world challenges, we only use 64 classes (Intersection classes of BURST Train subset and COCO dataset, without LVIS dataset) annotations data training, and testing on BURST test set data and get 61.4 OWTAall, ranking 1st in the benchmark. Our code will be released to facilitate future research.
|
https://arxiv.org/abs/2308.04598v1
|
2308.04598
|
2023-08-08
|
cybersecurity
|
1st Place Solution for ECCV 2022 OOD-CV Challenge Image Classification Track
|
OOD-CV challenge is an out-of-distribution generalization task. In this challenge, our core solution can be summarized as that Noisy Label Learning Is A Strong Test-Time Domain Adaptation Optimizer. Briefly speaking, our main pipeline can be divided into two stages, a pre-training stage for domain generalization and a test-time training stage for domain adaptation. We only exploit labeled source data in the pre-training stage and only exploit unlabeled target data in the test-time training stage. In the pre-training stage, we propose a simple yet effective Mask-Level Copy-Paste data augmentation strategy to enhance out-of-distribution generalization ability so as to resist shape, pose, context, texture, occlusion, and weather domain shifts in this challenge. In the test-time training stage, we use the pre-trained model to assign noisy label for the unlabeled target data, and propose a Label-Periodically-Updated DivideMix method for noisy label learning. After integrating Test-Time Augmentation and Model Ensemble strategies, our solution ranks the first place on the Image Classification Leaderboard of the OOD-CV Challenge. Code will be released in https://github.com/hikvision-research/OOD-CV.
|
https://arxiv.org/abs/2301.04795v1
|
2301.04795
|
2023-01-12
|
cybersecurity
|
1st Place Solution for ECCV 2022 OOD-CV Challenge Object Detection Track
|
OOD-CV challenge is an out-of-distribution generalization task. To solve this problem in object detection track, we propose a simple yet effective Generalize-then-Adapt (G&A) framework, which is composed of a two-stage domain generalization part and a one-stage domain adaptation part. The domain generalization part is implemented by a Supervised Model Pretraining stage using source data for model warm-up and a Weakly Semi-Supervised Model Pretraining stage using both source data with box-level label and auxiliary data (ImageNet-1K) with image-level label for performance boosting. The domain adaptation part is implemented as a Source-Free Domain Adaptation paradigm, which only uses the pre-trained model and the unlabeled target data to further optimize in a self-supervised training manner. The proposed G&A framework help us achieve the first place on the object detection leaderboard of the OOD-CV challenge. Code will be released in https://github.com/hikvision-research/OOD-CV.
|
https://arxiv.org/abs/2301.04796v1
|
2301.04796
|
2023-01-12
|
cybersecurity
|
1st Place Solution for ICCV 2023 OmniObject3D Challenge: Sparse-View Reconstruction
|
In this report, we present the 1st place solution for ICCV 2023 OmniObject3D Challenge: Sparse-View Reconstruction. The challenge aims to evaluate approaches for novel view synthesis and surface reconstruction using only a few posed images of each object. We utilize Pixel-NeRF as the basic model, and apply depth supervision as well as coarse-to-fine positional encoding. The experiments demonstrate the effectiveness of our approach in improving sparse-view reconstruction quality. We ranked first in the final test with a PSNR of 25.44614.
|
https://arxiv.org/abs/2404.10441v1
|
2404.10441
|
2024-04-16
|
cybersecurity
|
1st Place Solution for ICDAR 2021 Competition on Mathematical Formula Detection
|
In this technical report, we present our 1st place solution for the ICDAR 2021 competition on mathematical formula detection (MFD). The MFD task has three key challenges including a large scale span, large variation of the ratio between height and width, and rich character set and mathematical expressions. Considering these challenges, we used Generalized Focal Loss (GFL), an anchor-free method, instead of the anchor-based method, and prove the Adaptive Training Sampling Strategy (ATSS) and proper Feature Pyramid Network (FPN) can well solve the important issue of scale variation. Meanwhile, we also found some tricks, e.g., Deformable Convolution Network (DCN), SyncBN, and Weighted Box Fusion (WBF), were effective in MFD task. Our proposed method ranked 1st in the final 15 teams.
|
https://arxiv.org/abs/2107.05534v1
|
2107.05534
|
2021-07-12
|
cybersecurity
|
1st Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation
|
Motion Expression guided Video Segmentation (MeViS), as an emerging task, poses many new challenges to the field of referring video object segmentation (RVOS). In this technical report, we investigated and validated the effectiveness of static-dominant data and frame sampling on this challenging setting. Our solution achieves a J&F score of 0.5447 in the competition phase and ranks 1st in the MeViS track of the PVUW Challenge. The code is available at: https://github.com/Tapall-AI/MeViS_Track_Solution_2024.
|
https://arxiv.org/abs/2406.07043v1
|
2406.07043
|
2024-06-11
|
cybersecurity
|
1st Place Solution for MOSE Track in CVPR 2024 PVUW Workshop: Complex Video Object Segmentation
|
Tracking and segmenting multiple objects in complex scenes has always been a challenge in the field of video object segmentation, especially in scenarios where objects are occluded and split into parts. In such cases, the definition of objects becomes very ambiguous. The motivation behind the MOSE dataset is how to clearly recognize and distinguish objects in complex scenes. In this challenge, we propose a semantic embedding video object segmentation model and use the salient features of objects as query representations. The semantic understanding helps the model to recognize parts of the objects and the salient feature captures the more discriminative features of the objects. Trained on a large-scale video object segmentation dataset, our model achieves first place (\textbf{84.45\%}) in the test set of PVUW Challenge 2024: Complex Video Object Segmentation Track.
|
https://arxiv.org/abs/2406.04600v1
|
2406.04600
|
2024-06-07
|
cybersecurity
|
1st Place Solution for PSG competition with ECCV'22 SenseHuman Workshop
|
Panoptic Scene Graph (PSG) generation aims to generate scene graph representations based on panoptic segmentation instead of rigid bounding boxes. Existing PSG methods utilize one-stage paradigm which simultaneously generates scene graphs and predicts semantic segmentation masks or two-stage paradigm that first adopt an off-the-shelf panoptic segmentor, then pairwise relationship prediction between these predicted objects. One-stage approach despite having a simplified training paradigm, its segmentation results are usually under-satisfactory, while two-stage approach lacks global context and leads to low performance on relation prediction. To bridge this gap, in this paper, we propose GRNet, a Global Relation Network in two-stage paradigm, where the pre-extracted local object features and their corresponding masks are fed into a transformer with class embeddings. To handle relation ambiguity and predicate classification bias caused by long-tailed distribution, we formulate relation prediction in the second stage as a multi-class classification task with soft label. We conduct comprehensive experiments on OpenPSG dataset and achieve the state-of-art performance on the leadboard. We also show the effectiveness of our soft label strategy for long-tailed classes in ablation studies. Our code has been released in https://github.com/wangqixun/mfpsg.
|
https://arxiv.org/abs/2302.02651v1
|
2302.02651
|
2023-02-06
|
cybersecurity
|
1st Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation
|
Video panoptic segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. We believe that the decoupling strategy proposed by DVIS enables more effective utilization of temporal information for both "thing" and "stuff" objects. In this report, we successfully validated the effectiveness of the decoupling strategy in video panoptic segmentation. Finally, our method achieved a VPQ score of 51.4 and 53.7 in the development and test phases, respectively, and ultimately ranked 1st in the VPS track of the 2nd PVUW Challenge. The code is available at https://github.com/zhang-tao-whu/DVIS
|
https://arxiv.org/abs/2306.04091v2
|
2306.04091
|
2023-06-07
|
cybersecurity
|
1st Place Solution for the 5th LSVOS Challenge: Video Instance Segmentation
|
Video instance segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. In this report, we present further improvements to the SOTA VIS method, DVIS. First, we introduce a denoising training strategy for the trainable tracker, allowing it to achieve more stable and accurate object tracking in complex and long videos. Additionally, we explore the role of visual foundation models in video instance segmentation. By utilizing a frozen VIT-L model pre-trained by DINO v2, DVIS demonstrates remarkable performance improvements. With these enhancements, our method achieves 57.9 AP and 56.0 AP in the development and test phases, respectively, and ultimately ranked 1st in the VIS track of the 5th LSVOS Challenge. The code will be available at https://github.com/zhang-tao-whu/DVIS.
|
https://arxiv.org/abs/2308.14392v1
|
2308.14392
|
2023-08-28
|
cybersecurity
|
1st Place Solution for the UVO Challenge on Image-based Open-World Segmentation 2021
|
We describe our two-stage instance segmentation framework we use to compete in the challenge. The first stage of our framework consists of an object detector, which generates object proposals in the format of bounding boxes. Then, the images and the detected bounding boxes are fed to the second stage, where a segmentation network is applied to segment the objects in the bounding boxes. We train all our networks in a class-agnostic way. Our approach achieves the first place in the UVO 2021 Image-based Open-World Segmentation Challenge.
|
https://arxiv.org/abs/2110.10239v1
|
2110.10239
|
2021-10-19
|
cybersecurity
|
1st Place Solution for Waymo Open Dataset Challenge -- 3D Detection and Domain Adaptation
|
In this technical report, we introduce our winning solution "HorizonLiDAR3D" for the 3D detection track and the domain adaptation track in Waymo Open Dataset Challenge at CVPR 2020. Many existing 3D object detectors include prior-based anchor box design to account for different scales and aspect ratios and classes of objects, which limits its capability of generalization to a different dataset or domain and requires post-processing (e.g. Non-Maximum Suppression (NMS)). We proposed a one-stage, anchor-free and NMS-free 3D point cloud object detector AFDet, using object key-points to encode the 3D attributes, and to learn an end-to-end point cloud object detection without the need of hand-engineering or learning the anchors. AFDet serves as a strong baseline in our winning solution and significant improvements are made over this baseline during the challenges. Specifically, we design stronger networks and enhance the point cloud data using densification and point painting. To leverage camera information, we append/paint additional attributes to each point by projecting them to camera space and gathering image-based perception information. The final detection performance also benefits from model ensemble and Test-Time Augmentation (TTA) in both the 3D detection track and the domain adaptation track. Our solution achieves the 1st place with 77.11% mAPH/L2 and 69.49% mAPH/L2 respectively on the 3D detection track and the domain adaptation track.
|
https://arxiv.org/abs/2006.15505v1
|
2006.15505
|
2020-06-28
|
cybersecurity
|
1st Place Solution for YouTubeVOS Challenge 2021:Video Instance Segmentation
|
Video Instance Segmentation (VIS) is a multi-task problem performing detection, segmentation, and tracking simultaneously. Extended from image set applications, video data additionally induces the temporal information, which, if handled appropriately, is very useful to identify and predict object motions. In this work, we design a unified model to mutually learn these tasks. Specifically, we propose two modules, named Temporally Correlated Instance Segmentation (TCIS) and Bidirectional Tracking (BiTrack), to take the benefit of the temporal correlation between the object's instance masks across adjacent frames. On the other hand, video data is often redundant due to the frame's overlap. Our analysis shows that this problem is particularly severe for the YoutubeVOS-VIS2021 data. Therefore, we propose a Multi-Source Data (MSD) training mechanism to compensate for the data deficiency. By combining these techniques with a bag of tricks, the network performance is significantly boosted compared to the baseline, and outperforms other methods by a considerable margin on the YoutubeVOS-VIS 2019 and 2021 datasets.
|
https://arxiv.org/abs/2106.06649v2
|
2106.06649
|
2021-06-12
|
cybersecurity
|
1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation
|
The task of referring video object segmentation aims to segment the object in the frames of a given video to which the referring expressions refer. Previous methods adopt multi-stage approach and design complex pipelines to obtain promising results. Recently, the end-to-end method based on Transformer has proved its superiority. In this work, we draw on the advantages of the above methods to provide a simple and effective pipeline for RVOS. Firstly, We improve the state-of-the-art one-stage method ReferFormer to obtain mask sequences that are strongly correlated with language descriptions. Secondly, based on a reliable and high-quality keyframe, we leverage the superior performance of video object segmentation model to further enhance the quality and temporal consistency of the mask results. Our single model reaches 70.3 J &F on the Referring Youtube-VOS validation set and 63.0 on the test set. After ensemble, we achieve 64.1 on the final leaderboard, ranking 1st place on CVPR2022 Referring Youtube-VOS challenge. Code will be available at https://github.com/Zhiweihhh/cvpr2022-rvos-challenge.git.
|
https://arxiv.org/abs/2212.14679v1
|
2212.14679
|
2022-12-27
|
cybersecurity
|
1st Place Solution in Google Universal Images Embedding
|
This paper presents the 1st place solution for the Google Universal Images Embedding Competition on Kaggle. The highlighted part of our solution is based on 1) A novel way to conduct training and fine-tuning; 2) The idea of a better ensemble in the pool of models that make embedding; 3) The potential trade-off between fine-tuning on high-resolution and overlapping patches; 4) The potential factors to work for the dynamic margin. Our solution reaches 0.728 in the private leader board, which achieve 1st place in Google Universal Images Embedding Competition.
|
https://arxiv.org/abs/2210.08473v1
|
2210.08473
|
2022-10-16
|
cybersecurity
|
1st Place Solution of Egocentric 3D Hand Pose Estimation Challenge 2023 Technical Report:A Concise Pipeline for Egocentric Hand Pose Reconstruction
|
This report introduce our work on Egocentric 3D Hand Pose Estimation workshop. Using AssemblyHands, this challenge focuses on egocentric 3D hand pose estimation from a single-view image. In the competition, we adopt ViT based backbones and a simple regressor for 3D keypoints prediction, which provides strong model baselines. We noticed that Hand-objects occlusions and self-occlusions lead to performance degradation, thus proposed a non-model method to merge multi-view results in the post-process stage. Moreover, We utilized test time augmentation and model ensemble to make further improvement. We also found that public dataset and rational preprocess are beneficial. Our method achieved 12.21mm MPJPE on test dataset, achieve the first place in Egocentric 3D Hand Pose Estimation challenge.
|
https://arxiv.org/abs/2310.04769v2
|
2310.04769
|
2023-10-07
|
cybersecurity
|
1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask
|
This article introduces the solutions of the team lvisTraveler for LVIS Challenge 2020. In this work, two characteristics of LVIS dataset are mainly considered: the long-tailed distribution and high quality instance segmentation mask. We adopt a two-stage training pipeline. In the first stage, we incorporate EQL and self-training to learn generalized representation. In the second stage, we utilize Balanced GroupSoftmax to promote the classifier, and propose a novel proposal assignment strategy and a new balanced mask loss for mask head to get more precise mask predictions. Finally, we achieve 41.5 and 41.2 AP on LVIS v1.0 val and test-dev splits respectively, outperforming the baseline based on X101-FPN-MaskRCNN by a large margin.
|
https://arxiv.org/abs/2009.01559v1
|
2009.01559
|
2020-09-03
|
cybersecurity
|
1st Place Solution of Multiview Egocentric Hand Tracking Challenge ECCV2024
|
Multi-view egocentric hand tracking is a challenging task and plays a critical role in VR interaction. In this report, we present a method that uses multi-view input images and camera extrinsic parameters to estimate both hand shape and pose. To reduce overfitting to the camera layout, we apply crop jittering and extrinsic parameter noise augmentation. Additionally, we propose an offline neural smoothing post-processing method to further improve the accuracy of hand position and pose. Our method achieves 13.92mm MPJPE on the Umetrack dataset and 21.66mm MPJPE on the HOT3D dataset.
|
https://arxiv.org/abs/2409.19362v2
|
2409.19362
|
2024-09-28
|
cybersecurity
|
1st Place Solution of The Robust Vision Challenge 2022 Semantic Segmentation Track
|
This report describes the winning solution to the Robust Vision Challenge (RVC) semantic segmentation track at ECCV 2022. Our method adopts the FAN-B-Hybrid model as the encoder and uses SegFormer as the segmentation framework. The model is trained on a composite dataset consisting of images from 9 datasets (ADE20K, Cityscapes, Mapillary Vistas, ScanNet, VIPER, WildDash 2, IDD, BDD, and COCO) with a simple dataset balancing strategy. All the original labels are projected to a 256-class unified label space, and the model is trained using a cross-entropy loss. Without significant hyperparameter tuning or any specific loss weighting, our solution ranks the first place on all the testing semantic segmentation benchmarks from multiple domains (ADE20K, Cityscapes, Mapillary Vistas, ScanNet, VIPER, and WildDash 2). The proposed method can serve as a strong baseline for the multi-domain segmentation task and benefit future works. Code will be available at https://github.com/lambert-x/RVC_Segmentation.
|
https://arxiv.org/abs/2210.12852v3
|
2210.12852
|
2022-10-23
|
cybersecurity
|
1$^{st}$ Place Solution of WWW 2025 EReL@MIR Workshop Multimodal CTR Prediction Challenge
|
The WWW 2025 EReL@MIR Workshop Multimodal CTR Prediction Challenge focuses on effectively applying multimodal embedding features to improve click-through rate (CTR) prediction in recommender systems. This technical report presents our 1$^{st}$ place winning solution for Task 2, combining sequential modeling and feature interaction learning to effectively capture user-item interactions. For multimodal information integration, we simply append the frozen multimodal embeddings to each item embedding. Experiments on the challenge dataset demonstrate the effectiveness of our method, achieving superior performance with a 0.9839 AUC on the leaderboard, much higher than the baseline model. Code and configuration are available in our GitHub repository and the checkpoint of our model can be found in HuggingFace.
|
https://arxiv.org/abs/2505.03543v1
|
2505.03543
|
2025-05-06
|
cybersecurity
|
1st Place Solutions for OpenImage2019 -- Object Detection and Instance Segmentation
|
This article introduces the solutions of the two champion teams, `MMfruit' for the detection track and `MMfruitSeg' for the segmentation track, in OpenImage Challenge 2019. It is commonly known that for an object detector, the shared feature at the end of the backbone is not appropriate for both classification and regression, which greatly limits the performance of both single stage detector and Faster RCNN \cite{ren2015faster} based detector. In this competition, we observe that even with a shared feature, different locations in one object has completely inconsistent performances for the two tasks. \textit{E.g. the features of salient locations are usually good for classification, while those around the object edge are good for regression.} Inspired by this, we propose the Decoupling Head (DH) to disentangle the object classification and regression via the self-learned optimal feature extraction, which leads to a great improvement. Furthermore, we adjust the soft-NMS algorithm to adj-NMS to obtain stable performance improvement. Finally, a well-designed ensemble strategy via voting the bounding box location and confidence is proposed. We will also introduce several training/inferencing strategies and a bag of tricks that give minor improvement. Given those masses of details, we train and aggregate 28 global models with various backbones, heads and 3+2 expert models, and achieves the 1st place on the OpenImage 2019 Object Detection Challenge on the both public and private leadboards. Given such good instance bounding box, we further design a simple instance-level semantic segmentation pipeline and achieve the 1st place on the segmentation challenge.
|
https://arxiv.org/abs/2003.07557v1
|
2003.07557
|
2020-03-17
|
cybersecurity
|
1st Place Solutions for RxR-Habitat Vision-and-Language Navigation Competition (CVPR 2022)
|
This report presents the methods of the winning entry of the RxR-Habitat Competition in CVPR 2022. The competition addresses the problem of Vision-and-Language Navigation in Continuous Environments (VLN-CE), which requires an agent to follow step-by-step natural language instructions to reach a target. We present a modular plan-and-control approach for the task. Our model consists of three modules: the candidate waypoints predictor (CWP), the history enhanced planner and the tryout controller. In each decision loop, CWP first predicts a set of candidate waypoints based on depth observations from multiple views. It can reduce the complexity of the action space and facilitate planning. Then, a history-enhanced planner is adopted to select one of the candidate waypoints as the subgoal. The planner additionally encodes historical memory to track the navigation progress, which is especially effective for long-horizon navigation. Finally, we propose a non-parametric heuristic controller named tryout to execute low-level actions to reach the planned subgoal. It is based on the trial-and-error mechanism which can help the agent to avoid obstacles and escape from getting stuck. All three modules work hierarchically until the agent stops. We further take several recent advances of Vision-and-Language Navigation (VLN) to improve the performance such as pretraining based on large-scale synthetic in-domain dataset, environment-level data augmentation and snapshot model ensemble. Our model won the RxR-Habitat Competition 2022, with 48% and 90% relative improvements over existing methods on NDTW and SR metrics respectively.
|
https://arxiv.org/abs/2206.11610v2
|
2206.11610
|
2022-06-23
|
cybersecurity
|
1st Place Solutions for the UVO Challenge 2022
|
This paper describes the approach we have taken in the challenge. We still adopted the two-stage scheme same as the last champion, that is, detection first and segmentation followed. We trained more powerful detector and segmentor separately. Besides, we also perform pseudo-label training on the test set, based on student-teacher framework and end-to-end transformer based object detection. The method ranks first on the 2nd Unidentified Video Objects (UVO) challenge, achieving AR@100 of 46.8, 64.7 and 32.2 in the limited data frame track, unlimited data frame track and video track respectively.
|
https://arxiv.org/abs/2210.09629v1
|
2210.09629
|
2022-10-18
|
cybersecurity
|
1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition
|
In this technical report, we briefly introduce the solution of our team "TAL-ai" for (Semi-) supervised Face detection in the low light condition in UG2+ Challenge in CVPR 2021. By conducting several experiments with popular image enhancement methods and image transfer methods, we pulled the low light image and the normal image to a more closer domain. And it is observed that using these data to training can achieve better performance. We also adapt several popular object detection frameworks, e.g., DetectoRS, Cascade-RCNN, and large backbone like Swin-transformer. Finally, we ensemble several models which achieved mAP 74.89 on the testing set, ranking 1st on the final leaderboard.
|
https://arxiv.org/abs/2107.00818v1
|
2107.00818
|
2021-07-02
|
cybersecurity
|
1st Place Solutions for UG2+ Challenge 2022 ATMOSPHERIC TURBULENCE MITIGATION
|
In this technical report, we briefly introduce the solution of our team ''summer'' for Atomospheric Turbulence Mitigation in UG$^2$+ Challenge in CVPR 2022. In this task, we propose a unified end-to-end framework to reconstruct a high quality image from distorted frames, which is mainly consists of a Restormer-based image reconstruction module and a NIMA-based image quality assessment module. Our framework is efficient and generic, which is adapted to both hot-air image and text pattern. Moreover, we elaborately synthesize more than 10 thousands of images to simulate atmospheric turbulence. And these images improve the robustness of the model. Finally, we achieve the average accuracy of 98.53\% on the reconstruction result of the text patterns, ranking 1st on the final leaderboard.
|
https://arxiv.org/abs/2210.16847v1
|
2210.16847
|
2022-10-30
|
cybersecurity
|
1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking
|
This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D tracking challenges. An efficient and pragmatic online tracking-by-detection framework named HorizonMOT is proposed for camera-based 2D tracking in the image space and LiDAR-based 3D tracking in the 3D world space. Within the tracking-by-detection paradigm, our trackers leverage our high-performing detectors used in the 2D/3D detection challenges and achieved 45.13% 2D MOTA/L2 and 63.45% 3D MOTA/L2 in the 2D/3D tracking challenges.
|
https://arxiv.org/abs/2006.15506v1
|
2006.15506
|
2020-06-28
|
cybersecurity
|
1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
|
In this technical report, we present our solutions of Waymo Open Dataset (WOD) Challenge 2020 - 2D Object Track. We adopt FPN as our basic framework. Cascade RCNN, stacked PAFPN Neck and Double-Head are used for performance improvements. In order to handle the small object detection problem in WOD, we use very large image scales for both training and testing. Using our methods, our team RW-TSDet achieved the 1st place in the 2D Object Detection Track.
|
https://arxiv.org/abs/2008.01365v1
|
2008.01365
|
2020-08-04
|
cybersecurity
|
1st Place Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: End-to-End Recognition of Out of Vocabulary Words
|
Scene text recognition has attracted increasing interest in recent years due to its wide range of applications in multilingual translation, autonomous driving, etc. In this report, we describe our solution to the Out of Vocabulary Scene Text Understanding (OOV-ST) Challenge, which aims to extract out-of-vocabulary (OOV) words from natural scene images. Our oCLIP-based model achieves 28.59\% in h-mean which ranks 1st in end-to-end OOV word recognition track of OOV Challenge in ECCV2022 TiE Workshop.
|
https://arxiv.org/abs/2209.00224v1
|
2209.00224
|
2022-09-01
|
cybersecurity
|
1st Place Solution to ECCV-TAO-2020: Detect and Represent Any Object for Tracking
|
We extend the classical tracking-by-detection paradigm to this tracking-any-object task. Solid detection results are first extracted from TAO dataset. Some state-of-the-art techniques like \textbf{BA}lanced-\textbf{G}roup \textbf{S}oftmax (\textbf{BAGS}\cite{li2020overcoming}) and DetectoRS\cite{qiao2020detectors} are integrated during detection. Then we learned appearance features to represent any object by training feature learning networks. We ensemble several models for improving detection and feature representation. Simple linking strategies with most similar appearance features and tracklet-level post association module are finally applied to generate final tracking results. Our method is submitted as \textbf{AOA} on the challenge website. Code is available at https://github.com/feiaxyt/Winner_ECCV20_TAO.
|
https://arxiv.org/abs/2101.08040v2
|
2101.08040
|
2021-01-20
|
cybersecurity
|
1st Place Solution to Google Landmark Retrieval 2020
|
This paper presents the 1st place solution to the Google Landmark Retrieval 2020 Competition on Kaggle. The solution is based on metric learning to classify numerous landmark classes, and uses transfer learning with two train datasets, fine-tuning on bigger images, adjusting loss weight for cleaner samples, and esemble to enhance the model's performance further. Finally, it scored 0.38677 mAP@100 on the private leaderboard.
|
https://arxiv.org/abs/2009.05132v1
|
2009.05132
|
2020-08-24
|
cybersecurity
|
1st Place Solution to ICDAR 2021 RRC-ICTEXT End-to-end Text Spotting and Aesthetic Assessment on Integrated Circuit
|
This paper presents our proposed methods to ICDAR 2021 Robust Reading Challenge - Integrated Circuit Text Spotting and Aesthetic Assessment (ICDAR RRC-ICTEXT 2021). For the text spotting task, we detect the characters on integrated circuit and classify them based on yolov5 detection model. We balance the lowercase and non-lowercase by using SynthText, generated data and data sampler. We adopt semi-supervised algorithm and distillation to furtherly improve the model's accuracy. For the aesthetic assessment task, we add a classification branch of 3 classes to differentiate the aesthetic classes of each character. Finally, we make model deployment to accelerate inference speed and reduce memory consumption based on NVIDIA Tensorrt. Our methods achieve 59.1 mAP on task 3.1 with 31 FPS and 306M memory (rank 1), 78.7\% F2 score on task 3.2 with 30 FPS and 306M memory (rank 1).
|
https://arxiv.org/abs/2104.03544v1
|
2104.03544
|
2021-04-08
|
cybersecurity
|
1st Place Solution to MultiEarth 2023 Challenge on Multimodal SAR-to-EO Image Translation
|
The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) aims to harness the substantial amount of remote sensing data gathered over extensive periods for the monitoring and analysis of Earth's ecosystems'health. The subtask, Multimodal SAR-to-EO Image Translation, involves the use of robust SAR data, even under adverse weather and lighting conditions, transforming it into high-quality, clear, and visually appealing EO data. In the context of the SAR2EO task, the presence of clouds or obstructions in EO data can potentially pose a challenge. To address this issue, we propose the Clean Collector Algorithm (CCA), designed to take full advantage of this cloudless SAR data and eliminate factors that may hinder the data learning process. Subsequently, we applied pix2pixHD for the SAR-to-EO translation and Restormer for image enhancement. In the final evaluation, the team 'CDRL' achieved an MAE of 0.07313, securing the top rank on the leaderboard.
|
https://arxiv.org/abs/2306.12626v1
|
2306.12626
|
2023-06-22
|
cybersecurity
|
1st Place Solution to NeurIPS 2022 Challenge on Visual Domain Adaptation
|
The Visual Domain Adaptation(VisDA) 2022 Challenge calls for an unsupervised domain adaptive model in semantic segmentation tasks for industrial waste sorting. In this paper, we introduce the SIA_Adapt method, which incorporates several methods for domain adaptive models. The core of our method in the transferable representation from large-scale pre-training. In this process, we choose a network architecture that differs from the state-of-the-art for domain adaptation. After that, self-training using pseudo-labels helps to make the initial adaptation model more adaptable to the target domain. Finally, the model soup scheme helped to improve the generalization performance in the target domain. Our method SIA_Adapt achieves 1st place in the VisDA2022 challenge. The code is available on https: //github.com/DaehanKim-Korea/VisDA2022_Winner_Solution.
|
https://arxiv.org/abs/2211.14596v1
|
2211.14596
|
2022-11-26
|
cybersecurity
|
1st Place Solution to Odyssey Emotion Recognition Challenge Task1: Tackling Class Imbalance Problem
|
Speech emotion recognition is a challenging classification task with natural emotional speech, especially when the distribution of emotion types is imbalanced in the training and test data. In this case, it is more difficult for a model to learn to separate minority classes, resulting in those sometimes being ignored or frequently misclassified. Previous work has utilised class weighted loss for training, but problems remain as it sometimes causes over-fitting for minor classes or under-fitting for major classes. This paper presents the system developed by a multi-site team for the participation in the Odyssey 2024 Emotion Recognition Challenge Track-1. The challenge data has the aforementioned properties and therefore the presented systems aimed to tackle these issues, by introducing focal loss in optimisation when applying class weighted loss. Specifically, the focal loss is further weighted by prior-based class weights. Experimental results show that combining these two approaches brings better overall performance, by sacrificing performance on major classes. The system further employs a majority voting strategy to combine the outputs of an ensemble of 7 models. The models are trained independently, using different acoustic features and loss functions - with the aim to have different properties for different data. Hence these models show different performance preferences on major classes and minor classes. The ensemble system output obtained the best performance in the challenge, ranking top-1 among 68 submissions. It also outperformed all single models in our set. On the Odyssey 2024 Emotion Recognition Challenge Task-1 data the system obtained a Macro-F1 score of 35.69% and an accuracy of 37.32%.
|
https://arxiv.org/abs/2405.20064v1
|
2405.20064
|
2024-05-30
|
cybersecurity
|
1st Place Solution to the 1st SkatingVerse Challenge
|
This paper presents the winning solution for the 1st SkatingVerse Challenge. We propose a method that involves several steps. To begin, we leverage the DINO framework to extract the Region of Interest (ROI) and perform precise cropping of the raw video footage. Subsequently, we employ three distinct models, namely Unmasked Teacher, UniformerV2, and InfoGCN, to capture different aspects of the data. By ensembling the prediction results based on logits, our solution attains an impressive leaderboard score of 95.73%.
|
https://arxiv.org/abs/2404.14032v1
|
2404.14032
|
2024-04-22
|
cybersecurity
|
1st Place Solution to the 8th HANDS Workshop Challenge -- ARCTIC Track: 3DGS-based Bimanual Category-agnostic Interaction Reconstruction
|
This report describes our 1st place solution to the 8th HANDS workshop challenge (ARCTIC track) in conjunction with ECCV 2024. In this challenge, we address the task of bimanual category-agnostic hand-object interaction reconstruction, which aims to generate 3D reconstructions of both hands and the object from a monocular video, without relying on predefined templates. This task is particularly challenging due to the significant occlusion and dynamic contact between the hands and the object during bimanual manipulation. We worked to resolve these issues by introducing a mask loss and a 3D contact loss, respectively. Moreover, we applied 3D Gaussian Splatting (3DGS) to this task. As a result, our method achieved a value of 38.69 in the main metric, CD$_h$, on the ARCTIC test set.
|
https://arxiv.org/abs/2409.19215v2
|
2409.19215
|
2024-09-28
|
cybersecurity
|
1st Place Solution to the EPIC-Kitchens Action Anticipation Challenge 2022
|
In this report, we describe the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2022. In this competition, we develop the following two approaches. 1) Anticipation Time Knowledge Distillation using the soft labels learned by the teacher model as knowledge to guide the student network to learn the information of anticipation time; 2) Verb-Noun Relation Module for building the relationship between verbs and nouns. Our method achieves state-of-the-art results on the testing set of EPIC-Kitchens Action Anticipation Challenge 2022.
|
https://arxiv.org/abs/2207.05730v1
|
2207.05730
|
2022-07-10
|
cybersecurity
|
1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification
|
This paper presents our proposed methods for domain adaptive pedestrian re-identification (Re-ID) task in Visual Domain Adaptation Challenge (VisDA-2020). Considering the large gap between the source domain and target domain, we focused on solving two biases that influenced the performance on domain adaptive pedestrian Re-ID and proposed a two-stage training procedure. At the first stage, a baseline model is trained with images transferred from source domain to target domain and from single camera to multiple camera styles. Then we introduced a domain adaptation framework to train the model on source data and target data simultaneously. Different pseudo label generation strategies are adopted to continuously improve the discriminative ability of the model. Finally, with multiple models ensembled and additional post processing approaches adopted, our methods achieve 76.56% mAP and 84.25% rank-1 on the test set. Codes are available at https://github.com/vimar-gu/Bias-Eliminate-DA-ReID
|
https://arxiv.org/abs/2012.13498v1
|
2012.13498
|
2020-12-25
|
cybersecurity
|
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation
|
The third Pixel-level Video Understanding in the Wild (PVUW CVPR 2024) challenge aims to advance the state of art in video understanding through benchmarking Video Panoptic Segmentation (VPS) and Video Semantic Segmentation (VSS) on challenging videos and scenes introduced in the large-scale Video Panoptic Segmentation in the Wild (VIPSeg) test set and the large-scale Video Scene Parsing in the Wild (VSPW) test set, respectively. This paper details our research work that achieved the 1st place winner in the PVUW'24 VPS challenge, establishing state of art results in all metrics, including the Video Panoptic Quality (VPQ) and Segmentation and Tracking Quality (STQ). With minor fine-tuning our approach also achieved the 3rd place in the PVUW'24 VSS challenge ranked by the mIoU (mean intersection over union) metric and the first place ranked by the VC16 (16-frame video consistency) metric. Our winning solution stands on the shoulders of giant foundational vision transformer model (DINOv2 ViT-g) and proven multi-stage Decoupled Video Instance Segmentation (DVIS) frameworks for video understanding.
|
https://arxiv.org/abs/2406.05352v1
|
2406.05352
|
2024-06-08
|
cybersecurity
|
$1$-String $B_1$-VPG Representations of Planar Partial $3$-Trees and Some Subclasses
|
Planar partial $3$-trees are subgraphs of those planar graphs obtained by
repeatedly inserting a vertex of degree $3$ into a face. In this paper, we show
that planar partial $3$-trees have $1$-string $B_1$-VPG representations, i.e.,
representations where every vertex is represented by an orthogonal curve with
at most one bend, every two curves intersect at most once, and intersections of
curves correspond to edges in the graph. We also that some subclasses of planar
partial 3-trees have L-representations, i.e., a $B_1$-VPG representation where
every curve has the shape of an L.
|
http://arxiv.org/abs/1506.07246v1
|
1506.07246
|
2015-06-24
|
cybersecurity
|
1st Solution Places for CVPR 2023 UG$^2$+ Challenge Track 2.2-Coded Target Restoration through Atmospheric Turbulence
|
In this technical report, we briefly introduce the solution of our team VIELab-HUST for coded target restoration through atmospheric turbulence in CVPR 2023 UG$^2$+ Track 2.2. In this task, we propose an efficient multi-stage framework to restore a high quality image from distorted frames. Specifically, each distorted frame is initially aligned using image registration to suppress geometric distortion. We subsequently select the sharpest set of registered frames by employing a frame selection approach based on image sharpness, and average them to produce an image that is largely free of geometric distortion, albeit with blurriness. A learning-based deblurring method is then applied to remove the residual blur in the averaged image. Finally, post-processing techniques are utilized to further enhance the quality of the output image. Our framework is capable of handling different kinds of coded target dataset provided in the final testing phase, and ranked 1st on the final leaderboard. Our code will be available at https://github.com/xsqhust/Turbulence_Removal.
|
https://arxiv.org/abs/2306.09379v1
|
2306.09379
|
2023-06-15
|
cybersecurity
|
1st Solution Places for CVPR 2023 UG$^{\textbf{2}}$+ Challenge Track 2.1-Text Recognition through Atmospheric Turbulence
|
In this technical report, we present the solution developed by our team VIELab-HUST for text recognition through atmospheric turbulence in Track 2.1 of the CVPR 2023 UG$^{2}$+ challenge. Our solution involves an efficient multi-stage framework that restores a high-quality image from distorted frames. Specifically, a frame selection algorithm based on sharpness is first utilized to select the sharpest set of distorted frames. Next, each frame in the selected frames is aligned to suppress geometric distortion through optical-flow-based image registration. Then, a region-based image fusion method with DT-CWT is utilized to mitigate the blur caused by the turbulence. Finally, a learning-based deartifacts method is applied to remove the artifacts in the fused image, generating a high-quality outuput. Our framework can handle both hot-air text dataset and turbulence text dataset provided in the final testing phase and achieved 1st place in text recognition accuracy. Our code will be available at https://github.com/xsqhust/Turbulence_Removal.
|
https://arxiv.org/abs/2306.08963v1
|
2306.08963
|
2023-06-15
|
cybersecurity
|
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
|
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.
|
https://arxiv.org/abs/2211.13508v2
|
2211.13508
|
2022-11-24
|
cybersecurity
|
1-subdivisions, fractional chromatic number and Hall ratio
|
The Hall ratio of a graph G is the maximum of |V(H)|/alpha(H) over all
subgraphs H of G. Clearly, the Hall ratio of a graph is a lower bound for the
fractional chromatic number. It has been asked whether conversely, the
fractional chromatic number is upper bounded by a function of the Hall ratio.
We answer this question in negative, by showing two results of independent
interest regarding 1-subdivisions (the 1-subdivision of a graph is obtained by
subdividing each edge exactly once).
* For every c > 0, every graph of sufficiently large average degree contains
as a subgraph the 1-subdivision of a graph of fractional chromatic number at
least c.
* For every d > 0, there exists a graph G of average degree at least d such
that every graph whose 1-subdivision appears as a subgraph of G has Hall ratio
at most 18.
We also discuss the consequences of these results in the context of graph
classes with bounded expansion.
|
http://arxiv.org/abs/1812.07327v2
|
1812.07327
|
2020-01-30
|
cybersecurity
|
1 Tbit/s/$λ$ Transmission Over a 130 km Link Consisting of Graded-Index 50 $μ$m Core Multi-Mode Fiber and 6LP Few-Mode Fiber
|
We demonstrate 1 Tbit/s/$\lambda$ single-span transmission over a heterogeneous link consisting of graded-index 50 $\mu$m core multi-mode fiber and 6LP few-mode fiber using a Kramers-Kronig receiver structure. Furthermore, the link budget increase by transmitting only three modes while employing more than three receivers is investigated.
|
https://arxiv.org/abs/2010.15498v1
|
2010.15498
|
2020-10-29
|
cybersecurity
|
1-Tb/s/λ Transmission over Record 10714-km AR-HCF
|
We present the first single-channel 1.001-Tb/s DP-36QAM-PCS recirculating transmission over 73 loops of 146.77-km ultra-low-loss & low-IMI DNANF-5 fiber, achieving a record transmission distance of 10,714.28 km.
|
https://arxiv.org/abs/2503.24313v2
|
2503.24313
|
2025-03-31
|
cybersecurity
|
1T-FeS$_2$$:$ a new type of two-dimensional metallic ferromagnet
|
Discovery of intrinsic two-dimensional (2D) magnetic materials is crucial for understanding the fundamentals of 2D magnetism and realizing next-generation magnetoelectronic and magneto-optical devices. Although significant efforts have been devoted to identifying 2D magnetism by exfoliating bulk magnetic layered materials, seldom studies are performed to synthesize ultra-thin magnetic materials directly for non-layered magnetic materials. Here, we report the successful synthesis of a new type of theoretically proposed 2D metallic ferromagnet 1T FeS2, through the molten-salt-assisted chemical vapor deposition (CVD) method. The long-range 2D ferromagnetic order is confirmed by the observation of a large anomalous Hall effect (AHE) and a hysteretic magnetoresistance. The experimentally detected out-of-plane ferromagnetic ordering is theoretically suported with Stoner criterion. Our findings open up new possibilities to search novel 2D ferromagnets in non-layered compounds and render opportunities for realizing realistic ultra-thin spintronic devices.
|
https://arxiv.org/abs/2202.00252v1
|
2202.00252
|
2022-02-01
|
cybersecurity
|
[1]Title: $Υ$ and $η_b$ mass shifts in nuclear matter and the $^{12}$C nucleus bound states, [2]Title: $Υ$ and $η_b$ mass shifts in nuclear matter and the nucleus bound states
|
[1]Abstract: This is a contribution for the PANIC 2021 Proceedings based on the articles, Eur. Phys. J. A 57, 259 (2021) and the accompanied article $[$arXiv:2109.08636 $[$hep-ph$]]$ (Hadron 2021 contribution). We have estimated for the first time the mass shifts of the $\Upsilon$ and $\eta_b$ mesons in symmetric nuclear matter by an SU(5) flavor symmetric effective Lagrangian approach, as well as the in-medium mass of $B^*$ meson by the quark-meson coupling (QMC) model. The attractive potentials for the $\Upsilon$- and $\eta_b$-nuclear matter are obtained, and one can expect for these mesons to form nuclear bound states. We have indeed found such nuclear bound states with $^{12}$C nucleus, where the results for the $^{12}$C nucleus bound state energies are new, and we report here for the first time. [2]Abstract: We estimate for the first time the mass shifts (scalar potentials) in symmetric nuclear matter of the $\Upsilon$ and $\eta_b$ mesons using an effective Lagrangian approach, as well as the in-medium mass of the $B^*$ meson by the quark-meson coupling model. The attractive potentials of both $\Upsilon$ and $\eta_b$ are expected to be strong enough for these mesons to be bound to the $^4$He nucleus, and we have obtained such nuclear bound state energies.
|
https://arxiv.org/abs/2109.08636v2
|
2109.08636
|
2021-09-17
|
cybersecurity
|
1-to-1 or 1-to-n? Investigating the effect of function inlining on binary similarity analysis
|
Binary similarity analysis is critical to many code-reuse-related issues and "1-to-1" mechanism is widely applied, where one function in a binary file is matched against one function in a source file or binary file. However, we discover that function mapping is a more complex problem of "1-to-n" or even "n-to-n" due to the existence of function inlining. In this paper, we investigate the effect of function inlining on binary similarity analysis. We first construct 4 inlining-oriented datasets for four similarity analysis tasks, including code search, OSS reuse detection, vulnerability detection, and patch presence test. Then, we further study the extent of function inlining, the performance of existing works under function inlining, and the effectiveness of existing inlining-simulation strategies. Results show that the proportion of function inlining can reach nearly 70%, while most existing works neglect it and use "1-to-1" mechanism. The mismatches cause a 30% loss in performance during code search and a 40% loss during vulnerability detection. Moreover, two existing inlining-simulation strategies can only recover 60% of the inlined functions. We discover that inlining is usually cumulative when optimization increases. Conditional inlining and incremental inlining are suggested to design low-cost and high-coverage inlining-simulation strategies.
|
https://arxiv.org/abs/2112.12928v2
|
2112.12928
|
2021-12-24
|
cybersecurity
|
1 to 2.4 micron Near-IR spectrum of the Giant Planet $\beta$ Pictoris b obtained with the Gemini Planet Imager
|
Using the Gemini Planet Imager (GPI) located at Gemini South, we measured the
near-infrared (1.0-2.4 micron) spectrum of the planetary companion to the
nearby, young star $\beta$ Pictoris. We compare the spectrum obtained with
currently published model grids and with known substellar objects and present
the best matching models as well as the best matching observed objects.
Comparing the empirical measurement of the bolometric luminosity to
evolutionary models, we find a mass of $12.9\pm0.2$ $\mathcal{M}_\mathrm{Jup}$,
an effective temperature of $1724\pm15$ K, a radius of $1.46\pm0.01$
$\mathcal{R}_\mathrm{Jup}$, and a surface gravity of $\log g = 4.18\pm0.01$
[dex] (cgs). The stated uncertainties are statistical errors only, and do not
incorporate any uncertainty on the evolutionary models. Using atmospheric
models, we find an effective temperature of $1700-1800$ K and a surface gravity
of $\log g = 3.5$-$4.0$ [dex] depending upon model. These values agree well
with other publications and with "hot-start" predictions from planetary
evolution models. Further, we find that the spectrum of $\beta$ Pic b best
matches a low-surface gravity L2$\pm$1 brown dwarf. Finally comparing the
spectrum to field brown dwarfs we find the the spectrum best matches 2MASS
J04062677-381210 and 2MASS J03552337+1133437.
|
http://arxiv.org/abs/1703.00011v1
|
1703.00011
|
2017-02-28
|
cybersecurity
|
\$1 Today or \$2 Tomorrow? The Answer is in Your Facebook Likes
|
In economics and psychology, delay discounting is often used to characterize
how individuals choose between a smaller immediate reward and a larger delayed
reward. People with higher delay discounting rate (DDR) often choose smaller
but more immediate rewards (a "today person"). In contrast, people with a lower
discounting rate often choose a larger future rewards (a "tomorrow person").
Since the ability to modulate the desire of immediate gratification for long
term rewards plays an important role in our decision-making, the lower
discounting rate often predicts better social, academic and health outcomes. In
contrast, the higher discounting rate is often associated with problematic
behaviors such as alcohol/drug abuse, pathological gambling and credit card
default. Thus, research on understanding and moderating delay discounting has
the potential to produce substantial societal benefits.
|
http://arxiv.org/abs/1703.07726v3
|
1703.07726
|
2017-03-22
|
cybersecurity
|
1 Trillion Token (1TT) Platform: A Novel Framework for Efficient Data Sharing and Compensation in Large Language Models
|
In this paper, we propose the 1 Trillion Token Platform (1TT Platform), a novel framework designed to facilitate efficient data sharing with a transparent and equitable profit-sharing mechanism. The platform fosters collaboration between data contributors, who provide otherwise non-disclosed datasets, and a data consumer, who utilizes these datasets to enhance their own services. Data contributors are compensated in monetary terms, receiving a share of the revenue generated by the services of the data consumer. The data consumer is committed to sharing a portion of the revenue with contributors, according to predefined profit-sharing arrangements. By incorporating a transparent profit-sharing paradigm to incentivize large-scale data sharing, the 1TT Platform creates a collaborative environment to drive the advancement of NLP and LLM technologies.
|
https://arxiv.org/abs/2409.20149v1
|
2409.20149
|
2024-09-30
|
cybersecurity
|
1-Uryson width and covers
|
We investigate the following question: Do there exist Riemannian polyhedra $X$ such that the 1-Uryson width of their universal covers $\mathrm{UW}_1(\widetilde{X})$ is bounded but $\mathrm{UW}_1(X)$ is arbitrarily large? We rule out two specific cases: when $\pi_1(X)$ is virtually cyclic and when $X$ is a Riemannian surface. More specifically, we show that if $X$ is a compact polyhedron with a virtually cyclic fundamental group, then its 1-Uryson width is bounded by the 1-Uryson width of its universal cover $\widetilde{X}$. Precisely: $$\mathrm{UW}_1(X) \leq 6 \cdot \mathrm{UW}_1(\widetilde{X}).$$ We show that if $X$ is a Riemannian surface with boundary then $$\mathrm{UW}_1(X) \leq \mathrm{UW}_1(\widetilde{X}).$$ Furthermore, we show that if there exist spaces $X$ for which $\mathrm{UW}_1(\widetilde{X})$ is bounded while $\mathrm{UW}_1(X)$ is arbitrarily large, then such examples must already appear in low dimensions. In particular, such $X$ can be found among Riemannian $2$-complexes.
|
https://arxiv.org/abs/2505.21126v1
|
2505.21126
|
2025-05-27
|
cybersecurity
|
$(1+\varepsilon)$-ANN Data Structure for Curves via Subspaces of Bounded Doubling Dimension
|
We consider the $(1+\varepsilon)$-Approximate Nearest Neighbour (ANN) Problem for polygonal curves in $d$-dimensional space under the Fr\'echet distance and ask to what extent known data structures for doubling spaces can be applied to this problem. Initially, this approach does not seem viable, since the doubling dimension of the target space is known to be unbounded -- even for well-behaved polygonal curves of constant complexity in one dimension. In order to overcome this, we identify a subspace of curves which has bounded doubling dimension and small Gromov-Hausdorff distance to the target space. We then apply state-of-the-art techniques for doubling spaces and show how to obtain a data structure for the $(1+\varepsilon)$-ANN problem for any set of parametrized polygonal curves. The expected preprocessing time needed to construct the data-structure is $F(d,k,S,\varepsilon)n\log n$ and the space used is $F(d,k,S,\varepsilon)n$, with a query time of $F(d,k,S,\varepsilon)\log n + F(d,k,S,\varepsilon)^{-\log(\varepsilon)}$, where $F(d,k,S,\varepsilon)=O\left(2^{O(d)}k\Phi(S)\varepsilon^{-1}\right)^k$ and $\Phi(S)$ denotes the spread of the set of vertices and edges of the curves in $S$. We extend these results to the realistic class of $c$-packed curves and show improved bounds for small values of $c$.
|
https://arxiv.org/abs/2307.08521v1
|
2307.08521
|
2023-07-17
|
cybersecurity
|
$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets
|
Anomaly detection is not an easy problem since distribution of anomalous samples is unknown a priori. We explore a novel method that gives a trade-off possibility between one-class and two-class approaches, and leads to a better performance on anomaly detection problems with small or non-representative anomalous samples. The method is evaluated using several data sets and compared to a set of conventional one-class and two-class approaches.
|
https://arxiv.org/abs/1906.06096v1
|
1906.06096
|
2019-06-14
|
cybersecurity
|
$1/\varphi$ Spectrum of the Stress Dynamics with the Bak-Tang-Wiesenfeld Sandpile
|
With the original Bak-Tang-Wisenefeld (BTW) sandpile we uncover the $1/\varphi$ noise in the mechanism maintaining self-organized criticality (SOC) - the question raised together with the concept of SOC. We posit that the dynamics of stress in the BTW sandpile follows quasi-cycles of graduate stress accumulation that end up with an abrupt stress-release and the drop of the system to subcritical state. In thermodynamic limit, the intra-cycle dynamics exhibits the $1/\varphi$ spectrum that extends infinitely and corresponds to the stress-release within the critical state.
|
https://arxiv.org/abs/2212.14726v3
|
2212.14726
|
2022-12-30
|
cybersecurity
|
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