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9,500 | Bypassing Captcha By Machine A Proof For Passing The Turing Test | cs.CV | For the last ten years, CAPTCHAs have been widely used by websites to prevent
their data being automatically updated by machines. By supposedly allowing only
humans to do so, CAPTCHAs take advantage of the reverse Turing test (TT),
knowing that humans are more intelligent than machines. Generally, CAPTCHAs
have defeate... | computer science |
9,501 | Scene Image is Non-Mutually Exclusive - A Fuzzy Qualitative Scene
Understanding | cs.CV | Ambiguity or uncertainty is a pervasive element of many real world decision
making processes. Variation in decisions is a norm in this situation when the
same problem is posed to different subjects. Psychological and metaphysical
research had proven that decision making by human is subjective. It is
influenced by many ... | computer science |
9,502 | An Unsupervised Ensemble-based Markov Random Field Approach to
Microscope Cell Image Segmentation | cs.CV | In this paper, we propose an approach to the unsupervised segmentation of
images using Markov Random Field. The proposed approach is based on the idea of
Bit Plane Slicing. We use the planes as initial labellings for an ensemble of
segmentations. With pixelwise voting, a robust segmentation approach can be
achieved, wh... | computer science |
9,503 | Salient Object Detection: A Survey | cs.CV | Detecting and segmenting salient objects in natural scenes, often referred to
as salient object detection, has attracted a lot of interest in computer
vision. While many models have been proposed and several applications have
emerged, yet a deep understanding of achievements and issues is lacking. We aim
to provide a c... | computer science |
9,504 | Intelligent Indoor Mobile Robot Navigation Using Stereo Vision | cs.RO | Majority of the existing robot navigation systems, which facilitate the use
of laser range finders, sonar sensors or artificial landmarks, has the ability
to locate itself in an unknown environment and then build a map of the
corresponding environment. Stereo vision, while still being a rapidly
developing technique in ... | computer science |
9,505 | Using Hankel Matrices for Dynamics-based Facial Emotion Recognition and
Pain Detection | cs.CV | This paper proposes a new approach to model the temporal dynamics of a
sequence of facial expressions. To this purpose, a sequence of Face Image
Descriptors (FID) is regarded as the output of a Linear Time Invariant (LTI)
system. The temporal dynamics of such sequence of descriptors are represented
by means of a Hankel... | computer science |
9,506 | Tree-based Visualization and Optimization for Image Collection | cs.MM | The visualization of an image collection is the process of displaying a
collection of images on a screen under some specific layout requirements. This
paper focuses on an important problem that is not well addressed by the
previous methods: visualizing image collections into arbitrary layout shapes
while arranging imag... | computer science |
9,507 | Kernelized Deep Convolutional Neural Network for Describing Complex
Images | cs.CV | With the impressive capability to capture visual content, deep convolutional
neural networks (CNN) have demon- strated promising performance in various
vision-based ap- plications, such as classification, recognition, and objec- t
detection. However, due to the intrinsic structure design of CNN, for images
with complex... | computer science |
9,508 | Recurrent Neural Networks for Driver Activity Anticipation via
Sensory-Fusion Architecture | cs.CV | Anticipating the future actions of a human is a widely studied problem in
robotics that requires spatio-temporal reasoning. In this work we propose a
deep learning approach for anticipation in sensory-rich robotics applications.
We introduce a sensory-fusion architecture which jointly learns to anticipate
and fuse info... | computer science |
9,509 | Feature Evaluation of Deep Convolutional Neural Networks for Object
Recognition and Detection | cs.CV | In this paper, we evaluate convolutional neural network (CNN) features using
the AlexNet architecture and very deep convolutional network (VGGNet)
architecture. To date, most CNN researchers have employed the last layers
before output, which were extracted from the fully connected feature layers.
However, since it is u... | computer science |
9,510 | PERCH: Perception via Search for Multi-Object Recognition and
Localization | cs.CV | In many robotic domains such as flexible automated manufacturing or personal
assistance, a fundamental perception task is that of identifying and localizing
objects whose 3D models are known. Canonical approaches to this problem include
discriminative methods that find correspondences between feature descriptors
comput... | computer science |
9,511 | Heterogeneous Knowledge Transfer in Video Emotion Recognition,
Attribution and Summarization | cs.CV | Emotion is a key element in user-generated videos. However, it is difficult
to understand emotions conveyed in such videos due to the complex and
unstructured nature of user-generated content and the sparsity of video frames
expressing emotion. In this paper, for the first time, we study the problem of
transferring kno... | computer science |
9,512 | A diffusion and clustering-based approach for finding coherent motions
and understanding crowd scenes | cs.CV | This paper addresses the problem of detecting coherent motions in crowd
scenes and presents its two applications in crowd scene understanding: semantic
region detection and recurrent activity mining. It processes input motion
fields (e.g., optical flow fields) and produces a coherent motion filed, named
as thermal ener... | computer science |
9,513 | A Comparative Evaluation of Approximate Probabilistic Simulation and
Deep Neural Networks as Accounts of Human Physical Scene Understanding | cs.AI | Humans demonstrate remarkable abilities to predict physical events in complex
scenes. Two classes of models for physical scene understanding have recently
been proposed: "Intuitive Physics Engines", or IPEs, which posit that people
make predictions by running approximate probabilistic simulations in causal
mental model... | computer science |
9,514 | Yum-me: A Personalized Nutrient-based Meal Recommender System | cs.HC | Nutrient-based meal recommendations have the potential to help individuals
prevent or manage conditions such as diabetes and obesity. However, learning
people's food preferences and making recommendations that simultaneously appeal
to their palate and satisfy nutritional expectations are challenging. Existing
approache... | computer science |
9,515 | Low-Cost Scene Modeling using a Density Function Improves Segmentation
Performance | cs.CV | We propose a low cost and effective way to combine a free simulation software
and free CAD models for modeling human-object interaction in order to improve
human & object segmentation. It is intended for research scenarios related to
safe human-robot collaboration (SHRC) and interaction (SHRI) in the industrial
domain.... | computer science |
9,516 | Towards ontology driven learning of visual concept detectors | cs.IR | The maturity of deep learning techniques has led in recent years to a
breakthrough in object recognition in visual media. While for some specific
benchmarks, neural techniques seem to match if not outperform human judgement,
challenges are still open for detecting arbitrary concepts in arbitrary videos.
In this paper, ... | computer science |
9,517 | Learning to Poke by Poking: Experiential Learning of Intuitive Physics | cs.CV | We investigate an experiential learning paradigm for acquiring an internal
model of intuitive physics. Our model is evaluated on a real-world robotic
manipulation task that requires displacing objects to target locations by
poking. The robot gathered over 400 hours of experience by executing more than
100K pokes on dif... | computer science |
9,518 | Click Carving: Segmenting Objects in Video with Point Clicks | cs.CV | We present a novel form of interactive video object segmentation where a few
clicks by the user helps the system produce a full spatio-temporal segmentation
of the object of interest. Whereas conventional interactive pipelines take the
user's initialization as a starting point, we show the value in the system
taking th... | computer science |
9,519 | Augmenting Supervised Emotion Recognition with Rule-Based Decision Model | cs.HC | The aim of this research is development of rule based decision model for
emotion recognition. This research also proposes using the rules for augmenting
inter-corporal recognition accuracy in multimodal systems that use supervised
learning techniques. The classifiers for such learning based recognition
systems are susc... | computer science |
9,520 | Left/Right Hand Segmentation in Egocentric Videos | cs.HC | Wearable cameras allow people to record their daily activities from a
user-centered (First Person Vision) perspective. Due to their favorable
location, wearable cameras frequently capture the hands of the user, and may
thus represent a promising user-machine interaction tool for different
applications. Existent First P... | computer science |
9,521 | Faceless Person Recognition; Privacy Implications in Social Media | cs.CV | As we shift more of our lives into the virtual domain, the volume of data
shared on the web keeps increasing and presents a threat to our privacy. This
works contributes to the understanding of privacy implications of such data
sharing by analysing how well people are recognisable in social media data. To
facilitate a ... | computer science |
9,522 | Introspective Perception: Learning to Predict Failures in Vision Systems | cs.RO | As robots aspire for long-term autonomous operations in complex dynamic
environments, the ability to reliably take mission-critical decisions in
ambiguous situations becomes critical. This motivates the need to build systems
that have situational awareness to assess how qualified they are at that moment
to make a decis... | computer science |
9,523 | ShapeFit and ShapeKick for Robust, Scalable Structure from Motion | cs.CV | We introduce a new method for location recovery from pair-wise directions
that leverages an efficient convex program that comes with exact recovery
guarantees, even in the presence of adversarial outliers. When pairwise
directions represent scaled relative positions between pairs of views
(estimated for instance with e... | computer science |
9,524 | Facial Expression Recognition Using a Hybrid CNN-SIFT Aggregator | cs.CV | Deriving an effective facial expression recognition component is important
for a successful human-computer interaction system. Nonetheless, recognizing
facial expression remains a challenging task. This paper describes a novel
approach towards facial expression recognition task. The proposed method is
motivated by the ... | computer science |
9,525 | Can Peripheral Representations Improve Clutter Metrics on Complex
Scenes? | cs.CV | Previous studies have proposed image-based clutter measures that correlate
with human search times and/or eye movements. However, most models do not take
into account the fact that the effects of clutter interact with the foveated
nature of the human visual system: visual clutter further from the fovea has an
increasin... | computer science |
9,526 | Title Generation for User Generated Videos | cs.CV | A great video title describes the most salient event compactly and captures
the viewer's attention. In contrast, video captioning tends to generate
sentences that describe the video as a whole. Although generating a video title
automatically is a very useful task, it is much less addressed than video
captioning. We add... | computer science |
9,527 | Automation of Pedestrian Tracking in a Crowded Situation | cs.CV | Studies on microscopic pedestrian requires large amounts of trajectory data
from real-world pedestrian crowds. Such data collection, if done manually,
needs tremendous effort and is very time consuming. Though many studies have
asserted the possibility of automating this task using video cameras, we found
that only a f... | computer science |
9,528 | A Tube-and-Droplet-based Approach for Representing and Analyzing Motion
Trajectories | cs.CV | Trajectory analysis is essential in many applications. In this paper, we
address the problem of representing motion trajectories in a highly informative
way, and consequently utilize it for analyzing trajectories. Our approach first
leverages the complete information from given trajectories to construct a
thermal trans... | computer science |
9,529 | The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to
Foster Reproducible Research | cs.RO | Robotic challenges like the Amazon Picking Challenge (APC) or the DARPA
Challenges are an established and important way to drive scientific progress.
They make research comparable on a well-defined benchmark with equal test
conditions for all participants. However, such challenge events occur only
occasionally, are lim... | computer science |
9,530 | Deep-Learned Collision Avoidance Policy for Distributed Multi-Agent
Navigation | cs.AI | High-speed, low-latency obstacle avoidance that is insensitive to sensor
noise is essential for enabling multiple decentralized robots to function
reliably in cluttered and dynamic environments. While other distributed
multi-agent collision avoidance systems exist, these systems require online
geometric optimization wh... | computer science |
9,531 | A new algorithm for identity verification based on the analysis of a
handwritten dynamic signature | cs.CV | Identity verification based on authenticity assessment of a handwritten
signature is an important issue in biometrics. There are many effective methods
for signature verification taking into account dynamics of a signing process.
Methods based on partitioning take a very important place among them. In this
paper we pro... | computer science |
9,532 | Dynamic Probabilistic Network Based Human Action Recognition | cs.CV | This paper examines use of dynamic probabilistic networks (DPN) for human
action recognition. The actions of lifting objects and walking in the room,
sitting in the room and neutral standing pose were used for testing the
classification. The research used the dynamic interrelation between various
different regions of i... | computer science |
9,533 | Leveraging Video Descriptions to Learn Video Question Answering | cs.CV | We propose a scalable approach to learn video-based question answering (QA):
answer a "free-form natural language question" about a video content. Our
approach automatically harvests a large number of videos and descriptions
freely available online. Then, a large number of candidate QA pairs are
automatically generated... | computer science |
9,534 | T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects | cs.CV | We introduce T-LESS, a new public dataset for estimating the 6D pose, i.e.
translation and rotation, of texture-less rigid objects. The dataset features
thirty industry-relevant objects with no significant texture and no
discriminative color or reflectance properties. The objects exhibit symmetries
and mutual similarit... | computer science |
9,535 | Perceptually Optimized Image Rendering | cs.CV | We develop a framework for rendering photographic images, taking into account
display limitations, so as to optimize perceptual similarity between the
rendered image and the original scene. We formulate this as a constrained
optimization problem, in which we minimize a measure of perceptual
dissimilarity, the Normalize... | computer science |
9,536 | Sequence-based Multimodal Apprenticeship Learning For Robot Perception
and Decision Making | cs.RO | Apprenticeship learning has recently attracted a wide attention due to its
capability of allowing robots to learn physical tasks directly from
demonstrations provided by human experts. Most previous techniques assumed that
the state space is known a priori or employed simple state representations that
usually suffer fr... | computer science |
9,537 | Learning Social Affordance Grammar from Videos: Transferring Human
Interactions to Human-Robot Interactions | cs.RO | In this paper, we present a general framework for learning social affordance
grammar as a spatiotemporal AND-OR graph (ST-AOG) from RGB-D videos of human
interactions, and transfer the grammar to humanoids to enable a real-time
motion inference for human-robot interaction (HRI). Based on Gibbs sampling,
our weakly supe... | computer science |
9,538 | Sparse Depth Sensing for Resource-Constrained Robots | cs.RO | We consider the case in which a robot has to navigate in an unknown
environment but does not have enough on-board power or payload to carry a
traditional depth sensor (e.g., a 3D lidar) and thus can only acquire a few
(point-wise) depth measurements. We address the following question: is it
possible to reconstruct the ... | computer science |
9,539 | Learning Correspondence Structures for Person Re-identification | cs.CV | This paper addresses the problem of handling spatial misalignments due to
camera-view changes or human-pose variations in person re-identification. We
first introduce a boosting-based approach to learn a correspondence structure
which indicates the patch-wise matching probabilities between images from a
target camera p... | computer science |
9,540 | Transfer learning for music classification and regression tasks | cs.CV | In this paper, we present a transfer learning approach for music
classification and regression tasks. We propose to use a pre-trained convnet
feature, a concatenated feature vector using the activations of feature maps of
multiple layers in a trained convolutional network. We show how this convnet
feature can serve as ... | computer science |
9,541 | Sharing deep generative representation for perceived image
reconstruction from human brain activity | cs.AI | Decoding human brain activities via functional magnetic resonance imaging
(fMRI) has gained increasing attention in recent years. While encouraging
results have been reported in brain states classification tasks, reconstructing
the details of human visual experience still remains difficult. Two main
challenges that hin... | computer science |
9,542 | Quantum Mechanical Approach to Modelling Reliability of Sensor Reports | cs.OH | Dempster-Shafer evidence theory is wildly applied in multi-sensor data
fusion. However, lots of uncertainty and interference exist in practical
situation, especially in the battle field. It is still an open issue to model
the reliability of sensor reports. Many methods are proposed based on the
relationship among colle... | computer science |
9,543 | AirSim: High-Fidelity Visual and Physical Simulation for Autonomous
Vehicles | cs.RO | Developing and testing algorithms for autonomous vehicles in real world is an
expensive and time consuming process. Also, in order to utilize recent advances
in machine intelligence and deep learning we need to collect a large amount of
annotated training data in a variety of conditions and environments. We present
a n... | computer science |
9,544 | Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring
Algorithms in Whole Slide Images of Breast Cancer Tissues | cs.CV | Evaluating expression of the Human epidermal growth factor receptor 2 (Her2)
by visual examination of immunohistochemistry (IHC) on invasive breast cancer
(BCa) is a key part of the diagnostic assessment of BCa due to its recognised
importance as a predictive and prognostic marker in clinical practice. However,
visual ... | computer science |
9,545 | How a General-Purpose Commonsense Ontology can Improve Performance of
Learning-Based Image Retrieval | cs.AI | The knowledge representation community has built general-purpose ontologies
which contain large amounts of commonsense knowledge over relevant aspects of
the world, including useful visual information, e.g.: "a ball is used by a
football player", "a tennis player is located at a tennis court". Current
state-of-the-art ... | computer science |
9,546 | Towards Visual Ego-motion Learning in Robots | cs.RO | Many model-based Visual Odometry (VO) algorithms have been proposed in the
past decade, often restricted to the type of camera optics, or the underlying
motion manifold observed. We envision robots to be able to learn and perform
these tasks, in a minimally supervised setting, as they gain more experience.
To this end,... | computer science |
9,547 | Enhanced discrete particle swarm optimization path planning for UAV
vision-based surface inspection | cs.RO | In built infrastructure monitoring, an efficient path planning algorithm is
essential for robotic inspection of large surfaces using computer vision. In
this work, we first formulate the inspection path planning problem as an
extended travelling salesman problem (TSP) in which both the coverage and
obstacle avoidance w... | computer science |
9,548 | Comparing Neural and Attractiveness-based Visual Features for Artwork
Recommendation | cs.IR | Advances in image processing and computer vision in the latest years have
brought about the use of visual features in artwork recommendation. Recent
works have shown that visual features obtained from pre-trained deep neural
networks (DNNs) perform very well for recommending digital art. Other recent
works have shown t... | computer science |
9,549 | NO Need to Worry about Adversarial Examples in Object Detection in
Autonomous Vehicles | cs.CV | It has been shown that most machine learning algorithms are susceptible to
adversarial perturbations. Slightly perturbing an image in a carefully chosen
direction in the image space may cause a trained neural network model to
misclassify it. Recently, it was shown that physical adversarial examples
exist: printing pert... | computer science |
9,550 | Learning Photography Aesthetics with Deep CNNs | cs.CV | Automatic photo aesthetic assessment is a challenging artificial intelligence
task. Existing computational approaches have focused on modeling a single
aesthetic score or a class (good or bad), however these do not provide any
details on why the photograph is good or bad, or which attributes contribute to
the quality o... | computer science |
9,551 | Disentangling Motion, Foreground and Background Features in Videos | cs.CV | This paper introduces an unsupervised framework to extract semantically rich
features for video representation. Inspired by how the human visual system
groups objects based on motion cues, we propose a deep convolutional neural
network that disentangles motion, foreground and background information. The
proposed archit... | computer science |
9,552 | Robust Rigid Point Registration based on Convolution of Adaptive
Gaussian Mixture Models | cs.CV | Matching 3D rigid point clouds in complex environments robustly and
accurately is still a core technique used in many applications. This paper
proposes a new architecture combining error estimation from sample covariances
and dual global probability alignment based on the convolution of adaptive
Gaussian Mixture Models... | computer science |
9,553 | Fast Preprocessing for Robust Face Sketch Synthesis | cs.CV | Exemplar-based face sketch synthesis methods usually meet the challenging
problem that input photos are captured in different lighting conditions from
training photos. The critical step causing the failure is the search of similar
patch candidates for an input photo patch. Conventional illumination invariant
patch dist... | computer science |
9,554 | CREST: Convolutional Residual Learning for Visual Tracking | cs.CV | Discriminative correlation filters (DCFs) have been shown to perform
superiorly in visual tracking. They only need a small set of training samples
from the initial frame to generate an appearance model. However, existing DCFs
learn the filters separately from feature extraction, and update these filters
using a moving ... | computer science |
9,555 | Multibiometric Secure System Based on Deep Learning | cs.AI | In this paper, we propose a secure multibiometric system that uses deep
neural networks and error-correction coding. We present a feature-level fusion
framework to generate a secure multibiometric template from each user's
multiple biometrics. Two fusion architectures, fully connected architecture and
bilinear architec... | computer science |
9,556 | Deep Object-Centric Representations for Generalizable Robot Learning | cs.RO | Robotic manipulation in complex open-world scenarios requires both reliable
physical manipulation skills and effective and generalizable perception. In
this paper, we propose a method where general purpose pretrained visual models
serve as an object-centric prior for the perception system of a learned policy.
We devise... | computer science |
9,557 | More cat than cute? Interpretable Prediction of Adjective-Noun Pairs | cs.CV | The increasing availability of affect-rich multimedia resources has bolstered
interest in understanding sentiment and emotions in and from visual content.
Adjective-noun pairs (ANP) are a popular mid-level semantic construct for
capturing affect via visually detectable concepts such as "cute dog" or
"beautiful landscap... | computer science |
9,558 | Human Action Recognition System using Good Features and Multilayer
Perceptron Network | cs.CV | Human action recognition involves the characterization of human actions
through the automated analysis of video data and is integral in the development
of smart computer vision systems. However, several challenges like dynamic
backgrounds, camera stabilization, complex actions, occlusions etc. make action
recognition i... | computer science |
9,559 | Uncertainty-Aware Learning from Demonstration using Mixture Density
Networks with Sampling-Free Variance Modeling | cs.CV | In this paper, we propose an uncertainty-aware learning from demonstration
method by presenting a novel uncertainty estimation method utilizing a mixture
density network appropriate for modeling complex and noisy human behaviors. The
proposed uncertainty acquisition can be done with a single forward path without
Monte ... | computer science |
9,560 | Machine learning \& artificial intelligence in the quantum domain | cs.AI | Quantum information technologies, and intelligent learning systems, are both
emergent technologies that will likely have a transforming impact on our
society. The respective underlying fields of research -- quantum information
(QI) versus machine learning (ML) and artificial intelligence (AI) -- have
their own specific... | computer science |
9,561 | ClickBAIT: Click-based Accelerated Incremental Training of Convolutional
Neural Networks | cs.CV | Today's general-purpose deep convolutional neural networks (CNN) for image
classification and object detection are trained offline on large static
datasets. Some applications, however, will require training in real-time on
live video streams with a human-in-the-loop. We refer to this class of problem
as Time-ordered On... | computer science |
9,562 | Unsupervised state representation learning with robotic priors: a
robustness benchmark | cs.AI | Our understanding of the world depends highly on our capacity to produce
intuitive and simplified representations which can be easily used to solve
problems. We reproduce this simplification process using a neural network to
build a low dimensional state representation of the world from images acquired
by a robot. As i... | computer science |
9,563 | Commonsense Scene Semantics for Cognitive Robotics: Towards Grounding
Embodied Visuo-Locomotive Interactions | cs.RO | We present a commonsense, qualitative model for the semantic grounding of
embodied visuo-spatial and locomotive interactions. The key contribution is an
integrative methodology combining low-level visual processing with high-level,
human-centred representations of space and motion rooted in artificial
intelligence. We ... | computer science |
9,564 | Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single
Image | cs.RO | We consider the problem of dense depth prediction from a sparse set of depth
measurements and a single RGB image. Since depth estimation from monocular
images alone is inherently ambiguous and unreliable, to attain a higher level
of robustness and accuracy, we introduce additional sparse depth samples, which
are either... | computer science |
9,565 | Hierarchical Detail Enhancing Mesh-Based Shape Generation with 3D
Generative Adversarial Network | cs.GR | Automatic mesh-based shape generation is of great interest across a wide
range of disciplines, from industrial design to gaming, computer graphics and
various other forms of digital art. While most traditional methods focus on
primitive based model generation, advances in deep learning made it possible to
learn 3-dimen... | computer science |
9,566 | Human motion primitive discovery and recognition | cs.RO | We present a novel framework for the automatic discovery and recognition of
human motion primitives from motion capture data. Human motion primitives are
discovered by optimizing the 'motion flux', a quantity which depends on the
motion of a group of skeletal joints. Models of each primitive category are
computed via n... | computer science |
9,567 | Vision-based deep execution monitoring | cs.AI | Execution monitor of high-level robot actions can be effectively improved by
visual monitoring the state of the world in terms of preconditions and
postconditions that hold before and after the execution of an action.
Furthermore a policy for searching where to look at, either for verifying the
relations that specify t... | computer science |
9,569 | Privacy-Preserving Deep Inference for Rich User Data on The Cloud | cs.CV | Deep neural networks are increasingly being used in a variety of machine
learning applications applied to rich user data on the cloud. However, this
approach introduces a number of privacy and efficiency challenges, as the cloud
operator can perform secondary inferences on the available data. Recently,
advances in edge... | computer science |
9,570 | Texture Fuzzy Segmentation using Skew Divergence Adaptive Affinity
Functions | cs.CV | Digital image segmentation is the process of assigning distinct labels to
different objects in a digital image, and the fuzzy segmentation algorithm has
been successfully used in the segmentation of images from a wide variety of
sources. However, the traditional fuzzy segmentation algorithm fails to segment
objects tha... | computer science |
9,571 | Standard detectors aren't (currently) fooled by physical adversarial
stop signs | cs.CV | An adversarial example is an example that has been adjusted to produce the
wrong label when presented to a system at test time. If adversarial examples
existed that could fool a detector, they could be used to (for example) wreak
havoc on roads populated with smart vehicles. Recently, we described our
difficulties crea... | computer science |
9,572 | Deep Semantic Abstractions of Everyday Human Activities: On Commonsense
Representations of Human Interactions | cs.RO | We propose a deep semantic characterization of space and motion categorically
from the viewpoint of grounding embodied human-object interactions. Our key
focus is on an ontological model that would be adept to formalisation from the
viewpoint of commonsense knowledge representation, relational learning, and
qualitative... | computer science |
9,573 | A Survey on Optical Character Recognition System | cs.CV | Optical Character Recognition (OCR) has been a topic of interest for many
years. It is defined as the process of digitizing a document image into its
constituent characters. Despite decades of intense research, developing OCR
with capabilities comparable to that of human still remains an open challenge.
Due to this cha... | computer science |
9,574 | ADA: A Game-Theoretic Perspective on Data Augmentation for Object
Detection | cs.CV | The use of random perturbations of ground truth data, such as random
translation or scaling of bounding boxes, is a common heuristic used for data
augmentation that has been shown to prevent overfitting and improve
generalization. Since the design of data augmentation is largely guided by
reported best practices, it is... | computer science |
9,575 | Picasso, Matisse, or a Fake? Automated Analysis of Drawings at the
Stroke Level for Attribution and Authentication | eess.IV | This paper proposes a computational approach for analysis of strokes in line
drawings by artists. We aim at developing an AI methodology that facilitates
attribution of drawings of unknown authors in a way that is not easy to be
deceived by forged art. The methodology used is based on quantifying the
characteristics of... | computer science |
9,576 | GazeGAN - Unpaired Adversarial Image Generation for Gaze Estimation | cs.CV | Recent research has demonstrated the ability to estimate gaze on mobile
devices by performing inference on the image from the phone's front-facing
camera, and without requiring specialized hardware. While this offers wide
potential applications such as in human-computer interaction, medical diagnosis
and accessibility ... | computer science |
9,577 | Saliency Weighted Convolutional Features for Instance Search | cs.CV | This work explores attention models to weight the contribution of local
convolutional representations for the instance search task. We present a
retrieval framework based on bags of local convolutional features (BLCF) that
benefits from saliency weighting to build an efficient image representation.
The use of human vis... | computer science |
9,578 | Visual Explanation by High-Level Abduction: On Answer-Set Programming
Driven Reasoning about Moving Objects | cs.AI | We propose a hybrid architecture for systematically computing robust visual
explanation(s) encompassing hypothesis formation, belief revision, and default
reasoning with video data. The architecture consists of two tightly integrated
synergistic components: (1) (functional) answer set programming based abductive
reason... | computer science |
9,579 | Accurate reconstruction of image stimuli from human fMRI based on the
decoding model with capsule network architecture | cs.CV | In neuroscience, all kinds of computation models were designed to answer the
open question of how sensory stimuli are encoded by neurons and conversely, how
sensory stimuli can be decoded from neuronal activities. Especially, functional
Magnetic Resonance Imaging (fMRI) studies have made many great achievements
with th... | computer science |
9,580 | Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic
Experiences for Robot Action Execution | cs.AI | We present a novel deep neural network architecture for representing robot
experiences in an episodic-like memory which facilitates encoding, recalling,
and predicting action experiences. Our proposed unsupervised deep episodic
memory model 1) encodes observed actions in a latent vector space and, based on
this latent ... | computer science |
9,581 | Constraint-free Natural Image Reconstruction from fMRI Signals Based on
Convolutional Neural Network | cs.CV | In recent years, research on decoding brain activity based on functional
magnetic resonance imaging (fMRI) has made remarkable achievements. However,
constraint-free natural image reconstruction from brain activity is still a
challenge. The existing methods simplified the problem by using semantic prior
information or ... | computer science |
9,582 | Proceedings of eNTERFACE 2015 Workshop on Intelligent Interfaces | cs.HC | The 11th Summer Workshop on Multimodal Interfaces eNTERFACE 2015 was hosted
by the Numediart Institute of Creative Technologies of the University of Mons
from August 10th to September 2015. During the four weeks, students and
researchers from all over the world came together in the Numediart Institute of
the University... | computer science |
9,583 | PointCNN | cs.CV | We present a simple and general framework for feature learning from point
cloud. The key to the success of CNNs is the convolution operator that is
capable of leveraging spatially-local correlation in data represented densely
in grids (e.g. images). However, point cloud are irregular and unordered, thus
a direct convol... | computer science |
9,584 | Predicting Rapid Fire Growth (Flashover) Using Conditional Generative
Adversarial Networks | cs.AI | A flashover occurs when a fire spreads very rapidly through crevices due to
intense heat. Flashovers present one of the most frightening and challenging
fire phenomena to those who regularly encounter them: firefighters.
Firefighters' safety and lives often depend on their ability to predict
flashovers before they occu... | computer science |
9,585 | Personalized Machine Learning for Robot Perception of Affect and
Engagement in Autism Therapy | cs.RO | Robots have great potential to facilitate future therapies for children on
the autism spectrum. However, existing robots lack the ability to automatically
perceive and respond to human affect, which is necessary for establishing and
maintaining engaging interactions. Moreover, their inference challenge is made
harder b... | computer science |
9,586 | Dream Formulations and Deep Neural Networks: Humanistic Themes in the
Iconology of the Machine-Learned Image | cs.CY | This paper addresses the interpretability of deep learning-enabled image
recognition processes in computer vision science in relation to theories in art
history and cognitive psychology on the vision-related perceptual capabilities
of humans. Examination of what is determinable about the machine-learned image
in compar... | computer science |
9,587 | IONet: Learning to Cure the Curse of Drift in Inertial Odometry | cs.RO | Inertial sensors play a pivotal role in indoor localization, which in turn
lays the foundation for pervasive personal applications. However, low-cost
inertial sensors, as commonly found in smartphones, are plagued by bias and
noise, which leads to unbounded growth in error when accelerations are double
integrated to ob... | computer science |
9,588 | Shield: Fast, Practical Defense and Vaccination for Deep Learning using
JPEG Compression | cs.CV | The rapidly growing body of research in adversarial machine learning has
demonstrated that deep neural networks (DNNs) are highly vulnerable to
adversarially generated images. This underscores the urgent need for practical
defense that can be readily deployed to combat attacks in real-time. Observing
that many attack s... | computer science |
9,589 | Where is my Device? - Detecting the Smart Device's Wearing Location in
the Context of Active Safety for Vulnerable Road Users | cs.HC | This article describes an approach to detect the wearing location of smart
devices worn by pedestrians and cyclists. The detection, which is based solely
on the sensors of the smart devices, is important context-information which can
be used to parametrize subsequent algorithms, e.g. for dead reckoning or
intention det... | computer science |
9,590 | Measuring Conflict in a Multi-Source Environment as a Normal Measure | eess.SP | In a multi-source environment, each source has its own credibility. If there
is no external knowledge about credibility then we can use the information
provided by the sources to assess their credibility. In this paper, we propose
a way to measure conflict in a multi-source environment as a normal measure. We
examine o... | computer science |
9,591 | Fusion of an Ensemble of Augmented Image Detectors for Robust Object
Detection | cs.CV | A significant challenge in object detection is accurate identification of an
object's position in image space, whereas one algorithm with one set of
parameters is usually not enough, and the fusion of multiple algorithms and/or
parameters can lead to more robust results. Herein, a new computational
intelligence fusion ... | computer science |
9,592 | Centroid-based summarization of multiple documents: sentence extraction,
utility-based evaluation, and user studies | cs.CL | We present a multi-document summarizer, called MEAD, which generates
summaries using cluster centroids produced by a topic detection and tracking
system. We also describe two new techniques, based on sentence utility and
subsumption, which we have applied to the evaluation of both single and
multiple document summaries... | computer science |
9,593 | Robust Dialogue Understanding in HERALD | cs.CL | We tackle the problem of robust dialogue processing from the perspective of
language engineering. We propose an agent-oriented architecture that allows us
a flexible way of composing robust processors. Our approach is based on
Shoham's Agent Oriented Programming (AOP) paradigm. We will show how the AOP
agent model can ... | computer science |
9,594 | Improving the CSIEC Project and Adapting It to the English Teaching and
Learning in China | cs.CY | In this paper after short review of the CSIEC project initialized by us in
2003 we present the continuing development and improvement of the CSIEC project
in details, including the design of five new Microsoft agent characters
representing different virtual chatting partners and the limitation of
simulated dialogs in s... | computer science |
9,595 | Bio-linguistic transition and Baldwin effect in an evolutionary
naming-game model | cs.CL | We examine an evolutionary naming-game model where communicating agents are
equipped with an evolutionarily selected learning ability. Such a coupling of
biological and linguistic ingredients results in an abrupt transition: upon a
small change of a model control parameter a poorly communicating group of
linguistically... | computer science |
9,596 | Compositional Distributional Semantics with Compact Closed Categories
and Frobenius Algebras | cs.CL | This thesis contributes to ongoing research related to the categorical
compositional model for natural language of Coecke, Sadrzadeh and Clark in
three ways: Firstly, I propose a concrete instantiation of the abstract
framework based on Frobenius algebras (joint work with Sadrzadeh). The theory
improves shortcomings of... | computer science |
9,597 | Verifiable Source Code Documentation in Controlled Natural Language | cs.SE | Writing documentation about software internals is rarely considered a
rewarding activity. It is highly time-consuming and the resulting documentation
is fragile when the software is continuously evolving in a multi-developer
setting. Unfortunately, traditional programming environments poorly support the
writing and mai... | computer science |
9,598 | Exploration and Exploitation of Victorian Science in Darwin's Reading
Notebooks | cs.CL | Search in an environment with an uncertain distribution of resources involves
a trade-off between exploitation of past discoveries and further exploration.
This extends to information foraging, where a knowledge-seeker shifts between
reading in depth and studying new domains. To study this decision-making
process, we e... | computer science |
9,599 | Graded Entailment for Compositional Distributional Semantics | cs.CL | The categorical compositional distributional model of natural language
provides a conceptually motivated procedure to compute the meaning of
sentences, given grammatical structure and the meanings of its words. This
approach has outperformed other models in mainstream empirical language
processing tasks. However, until... | computer science |
9,600 | The Generalized Smallest Grammar Problem | cs.CL | The Smallest Grammar Problem -- the problem of finding the smallest
context-free grammar that generates exactly one given sequence -- has never
been successfully applied to grammatical inference. We investigate the reasons
and propose an extended formulation that seeks to minimize non-recursive
grammars, instead of str... | computer science |
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