Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
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25,502 | Image Retrieval Based on LBP Pyramidal Multiresolution using Reversible
Watermarking | cs.CV | In the medical field, images are increasingly used to facilitate diagnosis of
diseases. These images are stored in multimedia databases accompanied by doctor
s prescriptions and other information related to patients.Search for medical
images has become for clinical applications an essential tool to bring
effective aid ... | computer science |
25,503 | On Large-Scale Retrieval: Binary or n-ary Coding? | cs.CV | The growing amount of data available in modern-day datasets makes the need to
efficiently search and retrieve information. To make large-scale search
feasible, Distance Estimation and Subset Indexing are the main approaches.
Although binary coding has been popular for implementing both techniques, n-ary
coding (known a... | computer science |
25,504 | On 3D Face Reconstruction via Cascaded Regression in Shape Space | cs.CV | Cascaded regression has been recently applied to reconstructing 3D faces from
single 2D images directly in shape space, and achieved state-of-the-art
performance. This paper investigates thoroughly such cascaded regression based
3D face reconstruction approaches from four perspectives that are not well
studied yet: (i)... | computer science |
25,505 | LEWIS: Latent Embeddings for Word Images and their Semantics | cs.CV | The goal of this work is to bring semantics into the tasks of text
recognition and retrieval in natural images. Although text recognition and
retrieval have received a lot of attention in recent years, previous works have
focused on recognizing or retrieving exactly the same word used as a query,
without taking the sem... | computer science |
25,506 | Evaluating the visualization of what a Deep Neural Network has learned | cs.CV | Deep Neural Networks (DNNs) have demonstrated impressive performance in
complex machine learning tasks such as image classification or speech
recognition. However, due to their multi-layer nonlinear structure, they are
not transparent, i.e., it is hard to grasp what makes them arrive at a
particular classification or r... | computer science |
25,507 | From Facial Parts Responses to Face Detection: A Deep Learning Approach | cs.CV | In this paper, we propose a novel deep convolutional network (DCN) that
achieves outstanding performance on FDDB, PASCAL Face, and AFW. Specifically,
our method achieves a high recall rate of 90.99% on the challenging FDDB
benchmark, outperforming the state-of-the-art method by a large margin of
2.91%. Importantly, we ... | computer science |
25,508 | Understand Scene Categories by Objects: A Semantic Regularized Scene
Classifier Using Convolutional Neural Networks | cs.CV | Scene classification is a fundamental perception task for environmental
understanding in today's robotics. In this paper, we have attempted to exploit
the use of popular machine learning technique of deep learning to enhance scene
understanding, particularly in robotics applications. As scene images have
larger diversi... | computer science |
25,509 | Local Multi-Grouped Binary Descriptor with Ring-based Pooling
Configuration and Optimization | cs.CV | Local binary descriptors are attracting increasingly attention due to their
great advantages in computational speed, which are able to achieve real-time
performance in numerous image/vision applications. Various methods have been
proposed to learn data-dependent binary descriptors. However, most existing
binary descrip... | computer science |
25,510 | Attribute-Graph: A Graph based approach to Image Ranking | cs.CV | We propose a novel image representation, termed Attribute-Graph, to rank
images by their semantic similarity to a given query image. An Attribute-Graph
is an undirected fully connected graph, incorporating both local and global
image characteristics. The graph nodes characterise objects as well as the
overall scene con... | computer science |
25,511 | A Dual-Source Approach for 3D Pose Estimation from a Single Image | cs.CV | One major challenge for 3D pose estimation from a single RGB image is the
acquisition of sufficient training data. In particular, collecting large
amounts of training data that contain unconstrained images and are annotated
with accurate 3D poses is infeasible. We therefore propose to use two
independent training sourc... | computer science |
25,512 | Algebraic Clustering of Affine Subspaces | cs.CV | Subspace clustering is an important problem in machine learning with many
applications in computer vision and pattern recognition. Prior work has studied
this problem using algebraic, iterative, statistical, low-rank and sparse
representation techniques. While these methods have been applied to both linear
and affine s... | computer science |
25,513 | New Fuzzy LBP Features for Face Recognition | cs.CV | There are many Local texture features each very in way they implement and
each of the Algorithm trying improve the performance. An attempt is made in
this paper to represent a theoretically very simple and computationally
effective approach for face recognition. In our implementation the face image
is divided into 3x3 ... | computer science |
25,514 | Robust Object Tracking with a Hierarchical Ensemble Framework | cs.CV | Autonomous robots enjoy a wide popularity nowadays and have been applied in
many applications, such as home security, entertainment, delivery, navigation
and guidance. It is vital to robots to track objects accurately in these
applications, so it is necessary to focus on tracking algorithms to improve the
robustness an... | computer science |
25,515 | Is Image Super-resolution Helpful for Other Vision Tasks? | cs.CV | Despite the great advances made in the field of image super-resolution (ISR)
during the last years, the performance has merely been evaluated perceptually.
Thus, it is still unclear whether ISR is helpful for other vision tasks. In
this paper, we present the first comprehensive study and analysis of the
usefulness of I... | computer science |
25,516 | Automatic Concept Discovery from Parallel Text and Visual Corpora | cs.CV | Humans connect language and vision to perceive the world. How to build a
similar connection for computers? One possible way is via visual concepts,
which are text terms that relate to visually discriminative entities. We
propose an automatic visual concept discovery algorithm using parallel text and
visual corpora; it ... | computer science |
25,517 | Multi-Region Probabilistic Dice Similarity Coefficient using the
Aitchison Distance and Bipartite Graph Matching | cs.CV | Validation of image segmentation methods is of critical importance.
Probabilistic image segmentation is increasingly popular as it captures
uncertainty in the results. Image segmentation methods that support
multi-region (as opposed to binary) delineation are more favourable as they
capture interactions between the dif... | computer science |
25,518 | Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences | cs.CV | With the rapid proliferation of smart mobile devices, users now take millions
of photos every day. These include large numbers of clothing and accessory
images. We would like to answer questions like `What outfit goes well with this
pair of shoes?' To answer these types of questions, one has to go beyond
learning visua... | computer science |
25,519 | Learning Concept Embeddings with Combined Human-Machine Expertise | cs.CV | This paper presents our work on "SNaCK," a low-dimensional concept embedding
algorithm that combines human expertise with automatic machine similarity
kernels. Both parts are complimentary: human insight can capture relationships
that are not apparent from the object's visual similarity and the machine can
help relieve... | computer science |
25,520 | Incremental Loop Closure Verification by Guided Sampling | cs.CV | Loop closure detection, the task of identifying locations revisited by a
robot in a sequence of odometry and perceptual observations, is typically
formulated as a combination of two subtasks: (1) bag-of-words image retrieval
and (2) post-verification using RANSAC geometric verification. The main
contribution of this st... | computer science |
25,521 | Discriminative Map Retrieval Using View-Dependent Map Descriptor | cs.CV | Map retrieval, the problem of similarity search over a large collection of 2D
pointset maps previously built by mobile robots, is crucial for autonomous
navigation in indoor and outdoor environments. Bag-of-words (BoW) methods
constitute a popular approach to map retrieval; however, these methods have
extremely limited... | computer science |
25,522 | Self-localization Using Visual Experience Across Domains | cs.CV | In this study, we aim to solve the single-view robot self-localization
problem by using visual experience across domains. Although the bag-of-words
method constitutes a popular approach to single-view localization, it fails
badly when it's visual vocabulary is learned and tested in different domains.
Further, we are in... | computer science |
25,523 | Segment-Phrase Table for Semantic Segmentation, Visual Entailment and
Paraphrasing | cs.CV | We introduce Segment-Phrase Table (SPT), a large collection of bijective
associations between textual phrases and their corresponding segmentations.
Leveraging recent progress in object recognition and natural language
semantics, we show how we can successfully build a high-quality segment-phrase
table using minimal hu... | computer science |
25,524 | Multivariate Median Filters and Partial Differential Equations | cs.CV | Multivariate median filters have been proposed as generalisations of the
well-established median filter for grey-value images to multi-channel images.
As multivariate median, most of the recent approaches use the $L^1$ median,
i.e.\ the minimiser of an objective function that is the sum of distances to
all input points... | computer science |
25,525 | Amodal Completion and Size Constancy in Natural Scenes | cs.CV | We consider the problem of enriching current object detection systems with
veridical object sizes and relative depth estimates from a single image. There
are several technical challenges to this, such as occlusions, lack of
calibration data and the scale ambiguity between object size and distance.
These have not been a... | computer science |
25,526 | Robust video object tracking using particle filter with likelihood based
feature fusion and adaptive template updating | cs.CV | A robust algorithm solution is proposed for tracking an object in complex
video scenes. In this solution, the bootstrap particle filter (PF) is
initialized by an object detector, which models the time-evolving background of
the video signal by an adaptive Gaussian mixture. The motion of the object is
expressed by a Mar... | computer science |
25,527 | Fast Non-local Stereo Matching based on Hierarchical Disparity
Prediction | cs.CV | Stereo matching is the key step in estimating depth from two or more images.
Recently, some tree-based non-local stereo matching methods have been proposed,
which achieved state-of-the-art performance. The algorithms employed some tree
structures to aggregate cost and thus improved the performance and reduced the
coput... | computer science |
25,528 | Learning FRAME Models Using CNN Filters | cs.CV | The convolutional neural network (ConvNet or CNN) has proven to be very
successful in many tasks such as those in computer vision. In this conceptual
paper, we study the generative perspective of the discriminative CNN. In
particular, we propose to learn the generative FRAME (Filters, Random field,
And Maximum Entropy)... | computer science |
25,529 | Efficient Discriminative Nonorthogonal Binary Subspace with its
Application to Visual Tracking | cs.CV | One of the crucial problems in visual tracking is how the object is
represented. Conventional appearance-based trackers are using increasingly more
complex features in order to be robust. However, complex representations
typically not only require more computation for feature extraction, but also
make the state inferen... | computer science |
25,530 | Hyper-Fisher Vectors for Action Recognition | cs.CV | In this paper, a novel encoding scheme combining Fisher vector and
bag-of-words encodings has been proposed for recognizing action in videos. The
proposed Hyper-Fisher vector encoding is sum of local Fisher vectors which are
computed based on the traditional Bag-of-Words (BoW) encoding. Thus, the
proposed encoding is s... | computer science |
25,531 | Long-Range Trajectories from Global and Local Motion Representations | cs.CV | Motion is a fundamental cue for scene analysis and human activity understan-
ding in videos. It can be encoded in trajectories for tracking objects and for
action recognition, or in form of flow to address behaviour analysis in crowded
scenes. Each approach can only be applied on limited scenarios. We propose a
motion-... | computer science |
25,532 | Retinex filtering of foggy images: generation of a bulk set with
selection and ranking | cs.CV | In this paper we are proposing the use of GIMP Retinex, a filter of the GNU
Image Manipulation Program, for enhancing foggy images. This filter involves
adjusting four different parameters to find the output image which has to be
preferred according to some specific purposes. Aiming to obtain a processing,
which is abl... | computer science |
25,533 | Scalable Nonlinear Embeddings for Semantic Category-based Image
Retrieval | cs.CV | We propose a novel algorithm for the task of supervised discriminative
distance learning by nonlinearly embedding vectors into a low dimensional
Euclidean space. We work in the challenging setting where supervision is with
constraints on similar and dissimilar pairs while training. The proposed method
is derived by an ... | computer science |
25,534 | Light Field Reconstruction Using Shearlet Transform | cs.CV | In this article we develop an image based rendering technique based on light
field reconstruction from a limited set of perspective views acquired by
cameras. Our approach utilizes sparse representation of epipolar-plane images
in a directionally sensitive transform domain, obtained by an adapted discrete
shearlet tran... | computer science |
25,535 | Energy-Efficient Object Detection using Semantic Decomposition | cs.CV | Machine-learning algorithms offer immense possibilities in the development of
several cognitive applications. In fact, large scale machine-learning
classifiers now represent the state-of-the-art in a wide range of object
detection/classification problems. However, the network complexities of
large-scale classifiers pre... | computer science |
25,536 | Conditional Deep Learning for Energy-Efficient and Enhanced Pattern
Recognition | cs.CV | Deep learning neural networks have emerged as one of the most powerful
classification tools for vision related applications. However, the
computational and energy requirements associated with such deep nets can be
quite high, and hence their energy-efficient implementation is of great
interest. Although traditionally t... | computer science |
25,537 | Stats-Calculus Pose Descriptor Feeding A Discrete HMM Low-latency
Detection and Recognition System For 3D Skeletal Actions | cs.CV | Recognition of human actions, under low observational latency, is a growing
interest topic, nowadays. Many approaches have been represented based on a
provided set of 3D Cartesian coordinates system originated at a certain
specific point located on a root joint. In this paper, We will present a
statistical detection an... | computer science |
25,538 | Moving Object Detection in Video Using Saliency Map and Subspace
Learning | cs.CV | Moving object detection is a key to intelligent video analysis. On the one
hand, what moves is not only interesting objects but also noise and cluttered
background. On the other hand, moving objects without rich texture are prone
not to be detected. So there are undesirable false alarms and missed alarms in
many algori... | computer science |
25,539 | Online Object Tracking with Proposal Selection | cs.CV | Tracking-by-detection approaches are some of the most successful object
trackers in recent years. Their success is largely determined by the detector
model they learn initially and then update over time. However, under
challenging conditions where an object can undergo transformations, e.g.,
severe rotation, these meth... | computer science |
25,540 | A spatial compositional model (SCM) for linear unmixing and endmember
uncertainty estimation | cs.CV | The normal compositional model (NCM) has been extensively used in
hyperspectral unmixing. However, most of the previous research has focused on
estimation of endmembers and/or their variability. Also, little work has
employed spatial information in NCM. In this paper, we show that NCM can be
used for calculating the un... | computer science |
25,541 | General Dynamic Scene Reconstruction from Multiple View Video | cs.CV | This paper introduces a general approach to dynamic scene reconstruction from
multiple moving cameras without prior knowledge or limiting constraints on the
scene structure, appearance, or illumination. Existing techniques for dynamic
scene reconstruction from multiple wide-baseline camera views primarily focus
on accu... | computer science |
25,542 | Fast Single Image Super-Resolution | cs.CV | This paper addresses the problem of single image super-resolution (SR), which
consists of recovering a high resolution image from its blurred, decimated and
noisy version. The existing algorithms for single image SR use different
strategies to handle the decimation and blurring operators. In addition to the
traditional... | computer science |
25,543 | Data Association for an Adaptive Multi-target Particle Filter Tracking
System | cs.CV | This paper presents a novel approach to improve the accuracy of tracking
multiple objects in a static scene using a particle filter system by
introducing a data association step, a state queue for the collection of
tracked objects and adaptive parameters to the system. The data association
step makes use of the object ... | computer science |
25,544 | Off-the-Grid Recovery of Piecewise Constant Images from Few Fourier
Samples | cs.CV | We introduce a method to recover a continuous domain representation of a
piecewise constant two-dimensional image from few low-pass Fourier samples.
Assuming the edge set of the image is localized to the zero set of a
trigonometric polynomial, we show the Fourier coefficients of the partial
derivatives of the image sat... | computer science |
25,545 | Learning a Discriminative Model for the Perception of Realism in
Composite Images | cs.CV | What makes an image appear realistic? In this work, we are answering this
question from a data-driven perspective by learning the perception of visual
realism directly from large amounts of data. In particular, we train a
Convolutional Neural Network (CNN) model that distinguishes natural photographs
from automatically... | computer science |
25,546 | Effective Object Tracking in Unstructured Crowd Scenes | cs.CV | In this paper, we are presenting a rotation variant Oriented Texture Curve
(OTC) descriptor based mean shift algorithm for tracking an object in an
unstructured crowd scene. The proposed algorithm works by first obtaining the
OTC features for a manually selected object target, then a visual vocabulary is
created by usi... | computer science |
25,547 | Local Higher-Order Statistics (LHS) describing images with statistics of
local non-binarized pixel patterns | cs.CV | We propose a new image representation for texture categorization and facial
analysis, relying on the use of higher-order local differential statistics as
features. It has been recently shown that small local pixel pattern
distributions can be highly discriminative while being extremely efficient to
compute, which is in... | computer science |
25,548 | Human Action Recognition using Factorized Spatio-Temporal Convolutional
Networks | cs.CV | Human actions in video sequences are three-dimensional (3D) spatio-temporal
signals characterizing both the visual appearance and motion dynamics of the
involved humans and objects. Inspired by the success of convolutional neural
networks (CNN) for image classification, recent attempts have been made to
learn 3D CNNs f... | computer science |
25,549 | WHOI-Plankton- A Large Scale Fine Grained Visual Recognition Benchmark
Dataset for Plankton Classification | cs.CV | Planktonic organisms are of fundamental importance to marine ecosystems: they
form the basis of the food web, provide the link between the atmosphere and the
deep ocean, and influence global-scale biogeochemical cycles. Scientists are
increasingly using imaging-based technologies to study these creatures in their
natur... | computer science |
25,550 | Background Image Generation Using Boolean Operations | cs.CV | Tracking moving objects from a video sequence requires segmentation of these
objects from the background image. However, getting the actual background image
automatically without object detection and using only the video is difficult.
In this paper, we describe a novel algorithm that generates background from
real worl... | computer science |
25,551 | Cross-convolutional-layer Pooling for Image Recognition | cs.CV | Recent studies have shown that a Deep Convolutional Neural Network (DCNN)
pretrained on a large image dataset can be used as a universal image
descriptor, and that doing so leads to impressive performance for a variety of
image classification tasks. Most of these studies adopt activations from a
single DCNN layer, usua... | computer science |
25,552 | Efficient Hand Articulations Tracking using Adaptive Hand Model and
Depth map | cs.CV | Real-time hand articulations tracking is important for many applications such
as interacting with virtual / augmented reality devices or tablets. However,
most of existing algorithms highly rely on expensive and high power-consuming
GPUs to achieve real-time processing. Consequently, these systems are
inappropriate for... | computer science |
25,553 | Single Image Dehazing through Improved Atmospheric Light Estimation | cs.CV | Image contrast enhancement for outdoor vision is important for smart car
auxiliary transport systems. The video frames captured in poor weather
conditions are often characterized by poor visibility. Most image dehazing
algorithms consider to use a hard threshold assumptions or user input to
estimate atmospheric light. ... | computer science |
25,554 | GPU-Based Computation of 2D Least Median of Squares with Applications to
Fast and Robust Line Detection | cs.CV | The 2D Least Median of Squares (LMS) is a popular tool in robust regression
because of its high breakdown point: up to half of the input data can be
contaminated with outliers without affecting the accuracy of the LMS estimator.
The complexity of 2D LMS estimation has been shown to be $\Omega(n^2)$ where
$n$ is the tot... | computer science |
25,555 | Intensity-only optical compressive imaging using a multiply scattering
material and a double phase retrieval approach | cs.CV | In this paper, the problem of compressive imaging is addressed using natural
randomization by means of a multiply scattering medium. To utilize the medium
in this way, its corresponding transmission matrix must be estimated. To
calibrate the imager, we use a digital micromirror device (DMD) as a simple,
cheap, and high... | computer science |
25,556 | Visual Tracking via Nonnegative Regularization Multiple Locality Coding | cs.CV | This paper presents a novel object tracking method based on approximated
Locality-constrained Linear Coding (LLC). Rather than using a non-negativity
constraint on encoding coefficients to guarantee these elements nonnegative, in
this paper, the non-negativity constraint is substituted for a conventional
$\ell_2$ norm ... | computer science |
25,557 | Efficient Object Detection for High Resolution Images | cs.CV | Efficient generation of high-quality object proposals is an essential step in
state-of-the-art object detection systems based on deep convolutional neural
networks (DCNN) features. Current object proposal algorithms are
computationally inefficient in processing high resolution images containing
small objects, which mak... | computer science |
25,558 | Harvesting Discriminative Meta Objects with Deep CNN Features for Scene
Classification | cs.CV | Recent work on scene classification still makes use of generic CNN features
in a rudimentary manner. In this ICCV 2015 paper, we present a novel pipeline
built upon deep CNN features to harvest discriminative visual objects and parts
for scene classification. We first use a region proposal technique to generate
a set o... | computer science |
25,559 | Unsupervised Extraction of Video Highlights Via Robust Recurrent
Auto-encoders | cs.CV | With the growing popularity of short-form video sharing platforms such as
\em{Instagram} and \em{Vine}, there has been an increasing need for techniques
that automatically extract highlights from video. Whereas prior works have
approached this problem with heuristic rules or supervised learning, we present
an unsupervi... | computer science |
25,560 | Directional Global Three-part Image Decomposition | cs.CV | We consider the task of image decomposition and we introduce a new model
coined directional global three-part decomposition (DG3PD) for solving it. As
key ingredients of the DG3PD model, we introduce a discrete multi-directional
total variation norm and a discrete multi-directional G-norm. Using these novel
norms, the ... | computer science |
25,561 | Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets
for Future Tasks | cs.CV | How can we reuse existing knowledge, in the form of available datasets, when
solving a new and apparently unrelated target task from a set of unlabeled
data? In this work we make a first contribution to answer this question in the
context of image classification. We frame this quest as an active learning
problem and us... | computer science |
25,562 | Learning Deep Representations of Appearance and Motion for Anomalous
Event Detection | cs.CV | We present a novel unsupervised deep learning framework for anomalous event
detection in complex video scenes. While most existing works merely use
hand-crafted appearance and motion features, we propose Appearance and Motion
DeepNet (AMDN) which utilizes deep neural networks to automatically learn
feature representati... | computer science |
25,563 | Predicting Daily Activities From Egocentric Images Using Deep Learning | cs.CV | We present a method to analyze images taken from a passive egocentric
wearable camera along with the contextual information, such as time and day of
week, to learn and predict everyday activities of an individual. We collected a
dataset of 40,103 egocentric images over a 6 month period with 19 activity
classes and demo... | computer science |
25,564 | A Latent Source Model for Patch-Based Image Segmentation | cs.CV | Despite the popularity and empirical success of patch-based nearest-neighbor
and weighted majority voting approaches to medical image segmentation, there
has been no theoretical development on when, why, and how well these
nonparametric methods work. We bridge this gap by providing a theoretical
performance guarantee f... | computer science |
25,565 | Euclidean Auto Calibration of Camera Networks: Baseline Constraint
Removes Scale Ambiguity | cs.CV | Metric auto calibration of a camera network from multiple views has been
reported by several authors. Resulting 3D reconstruction recovers shape
faithfully, but not scale. However, preservation of scale becomes critical in
applications, such as multi-party telepresence, where multiple 3D scenes need
to be fused into a ... | computer science |
25,566 | Diverse Large-Scale ITS Dataset Created from Continuous Learning for
Real-Time Vehicle Detection | cs.CV | In traffic engineering, vehicle detectors are trained on limited datasets
resulting in poor accuracy when deployed in real world applications. Annotating
large-scale high quality datasets is challenging. Typically, these datasets
have limited diversity; they do not reflect the real-world operating
environment. There is... | computer science |
25,567 | Augmenting Bag-of-Words: Data-Driven Discovery of Temporal and
Structural Information for Activity Recognition | cs.CV | We present data-driven techniques to augment Bag of Words (BoW) models, which
allow for more robust modeling and recognition of complex long-term activities,
especially when the structure and topology of the activities are not known a
priori. Our approach specifically addresses the limitations of standard BoW
approache... | computer science |
25,568 | Egocentric Field-of-View Localization Using First-Person Point-of-View
Devices | cs.CV | We present a technique that uses images, videos and sensor data taken from
first-person point-of-view devices to perform egocentric field-of-view (FOV)
localization. We define egocentric FOV localization as capturing the visual
information from a person's field-of-view in a given environment and
transferring this infor... | computer science |
25,569 | Leveraging Context to Support Automated Food Recognition in Restaurants | cs.CV | The pervasiveness of mobile cameras has resulted in a dramatic increase in
food photos, which are pictures reflecting what people eat. In this paper, we
study how taking pictures of what we eat in restaurants can be used for the
purpose of automating food journaling. We propose to leverage the context of
where the pict... | computer science |
25,570 | DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer | cs.CV | Recently, there has been a flurry of industrial activity around logo
recognition, such as Ditto's service for marketers to track their brands in
user-generated images, and LogoGrab's mobile app platform for logo recognition.
However, relatively little academic or open-source logo recognition progress
has been made in t... | computer science |
25,571 | Simultaneous Deep Transfer Across Domains and Tasks | cs.CV | Recent reports suggest that a generic supervised deep CNN model trained on a
large-scale dataset reduces, but does not remove, dataset bias. Fine-tuning
deep models in a new domain can require a significant amount of labeled data,
which for many applications is simply not available. We propose a new CNN
architecture to... | computer science |
25,572 | Learning Data-driven Reflectance Priors for Intrinsic Image
Decomposition | cs.CV | We propose a data-driven approach for intrinsic image decomposition, which is
the process of inferring the confounding factors of reflectance and shading in
an image. We pose this as a two-stage learning problem. First, we train a model
to predict relative reflectance ordering between image patches (`brighter',
`darker... | computer science |
25,573 | Free-hand Sketch Synthesis with Deformable Stroke Models | cs.CV | We present a generative model which can automatically summarize the stroke
composition of free-hand sketches of a given category. When our model is fit to
a collection of sketches with similar poses, it discovers and learns the
structure and appearance of a set of coherent parts, with each part represented
by a group o... | computer science |
25,574 | Human Head Pose Estimation by Facial Features Location | cs.CV | We describe a method for estimating human head pose in a color image that
contains enough of information to locate the head silhouette and detect
non-trivial color edges of individual facial features. The method works by
spotting the human head on an arbitrary background, extracting the head
outline, and locating facia... | computer science |
25,575 | Where Is My Puppy? Retrieving Lost Dogs by Facial Features | cs.CV | A pet that goes missing is among many people's worst fears: a moment of
distraction is enough for a dog or a cat wandering off from home. Some measures
help matching lost animals to their owners; but automated visual recognition is
one that - although convenient, highly available, and low-cost - is
surprisingly overloo... | computer science |
25,576 | Dreaming More Data: Class-dependent Distributions over Diffeomorphisms
for Learned Data Augmentation | cs.CV | Data augmentation is a key element in training high-dimensional models. In
this approach, one synthesizes new observations by applying pre-specified
transformations to the original training data; e.g.~new images are formed by
rotating old ones. Current augmentation schemes, however, rely on manual
specification of the ... | computer science |
25,577 | Wavelet Frame Based Image Restoration Using Sparsity, Nonlocal and
Support Prior of Frame Coefficients | cs.CV | The wavelet frame systems have been widely investigated and applied for image
restoration and many other image processing problems over the past decades,
attributing to their good capability of sparsely approximating piece-wise
smooth functions such as images. Most wavelet frame based models exploit the
$l_1$ norm of f... | computer science |
25,578 | Learn to Evaluate Image Perceptual Quality Blindly from Statistics of
Self-similarity | cs.CV | Among the various image quality assessment (IQA) tasks, blind IQA (BIQA) is
particularly challenging due to the absence of knowledge about the reference
image and distortion type. Features based on natural scene statistics (NSS)
have been successfully used in BIQA, while the quality relevance of the feature
plays an es... | computer science |
25,579 | Temporal Dynamic Appearance Modeling for Online Multi-Person Tracking | cs.CV | Robust online multi-person tracking requires the correct associations of
online detection responses with existing trajectories. We address this problem
by developing a novel appearance modeling approach to provide accurate
appearance affinities to guide data association. In contrast to most existing
algorithms that onl... | computer science |
25,580 | DeepFix: A Fully Convolutional Neural Network for predicting Human Eye
Fixations | cs.CV | Understanding and predicting the human visual attentional mechanism is an
active area of research in the fields of neuroscience and computer vision. In
this work, we propose DeepFix, a first-of-its-kind fully convolutional neural
network for accurate saliency prediction. Unlike classical works which
characterize the sa... | computer science |
25,581 | Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion | cs.CV | The degradation of the acquired signal by Poisson noise is a common problem
for various imaging applications, such as medical imaging, night vision and
microscopy. Up to now, many state-of-the-art Poisson denoising techniques
mainly concentrate on achieving utmost performance, with little consideration
for the computat... | computer science |
25,582 | Spatial Semantic Regularisation for Large Scale Object Detection | cs.CV | Large scale object detection with thousands of classes introduces the problem
of many contradicting false positive detections, which have to be suppressed.
Class-independent non-maximum suppression has traditionally been used for this
step, but it does not scale well as the number of classes grows. Traditional
non-maxi... | computer science |
25,583 | Fast detection of multiple objects in traffic scenes with a common
detection framework | cs.CV | Traffic scene perception (TSP) aims to real-time extract accurate on-road
environment information, which in- volves three phases: detection of objects of
interest, recognition of detected objects, and tracking of objects in motion.
Since recognition and tracking often rely on the results from detection, the
ability to ... | computer science |
25,584 | Interactive multiclass segmentation using superpixel classification | cs.CV | This paper adresses the problem of interactive multiclass segmentation. We
propose a fast and efficient new interactive segmentation method called
Superpixel Classification-based Interactive Segmentation (SCIS). From a few
strokes drawn by a human user over an image, this method extracts relevant
semantic objects. To g... | computer science |
25,585 | Using Anatomical Markers for Left Ventricular Segmentation of Long Axis
Ultrasound Images | cs.CV | Left ventricular segmentation is essential for measuring left ventricular
function indices. Segmentation of one or several images requires an initial
guess of the contour. It is hypothesized here that creating an initial guess by
first detecting anatomical markers, would lead to correct detection of the
endocardium. Th... | computer science |
25,586 | Text-Attentional Convolutional Neural Networks for Scene Text Detection | cs.CV | Recent deep learning models have demonstrated strong capabilities for
classifying text and non-text components in natural images. They extract a
high-level feature computed globally from a whole image component (patch),
where the cluttered background information may dominate true text features in
the deep representatio... | computer science |
25,587 | Deep convolutional neural networks for pedestrian detection | cs.CV | Pedestrian detection is a popular research topic due to its paramount
importance for a number of applications, especially in the fields of
automotive, surveillance and robotics. Despite the significant improvements,
pedestrian detection is still an open challenge that calls for more and more
accurate algorithms. In the... | computer science |
25,588 | SemanticPaint: A Framework for the Interactive Segmentation of 3D Scenes | cs.CV | We present an open-source, real-time implementation of SemanticPaint, a
system for geometric reconstruction, object-class segmentation and learning of
3D scenes. Using our system, a user can walk into a room wearing a depth camera
and a virtual reality headset, and both densely reconstruct the 3D scene and
interactivel... | computer science |
25,589 | Wide-Area Image Geolocalization with Aerial Reference Imagery | cs.CV | We propose to use deep convolutional neural networks to address the problem
of cross-view image geolocalization, in which the geolocation of a ground-level
query image is estimated by matching to georeferenced aerial images. We use
state-of-the-art feature representations for ground-level images and introduce
a cross-v... | computer science |
25,590 | Better Exploiting OS-CNNs for Better Event Recognition in Images | cs.CV | Event recognition from still images is one of the most important problems for
image understanding. However, compared with object recognition and scene
recognition, event recognition has received much less research attention in
computer vision community. This paper addresses the problem of cultural event
recognition in ... | computer science |
25,591 | Multiresolution Search of the Rigid Motion Space for Intensity Based
Registration | cs.CV | We study the relation between the target functions of low-resolution and
high-resolution intensity-based registration for the class of rigid
transformations. Our results show that low resolution target values can tightly
bound the high-resolution target function in natural images. This can help with
analyzing and bette... | computer science |
25,592 | Fine-Grained Product Class Recognition for Assisted Shopping | cs.CV | Assistive solutions for a better shopping experience can improve the quality
of life of people, in particular also of visually impaired shoppers. We present
a system that visually recognizes the fine-grained product classes of items on
a shopping list, in shelves images taken with a smartphone in a grocery store.
Our s... | computer science |
25,593 | Dynamical spectral unmixing of multitemporal hyperspectral images | cs.CV | In this paper, we consider the problem of unmixing a time series of
hyperspectral images. We propose a dynamical model based on linear mixing
processes at each time instant. The spectral signatures and fractional
abundances of the pure materials in the scene are seen as latent variables, and
assumed to follow a general... | computer science |
25,594 | A Novel Approach for Human Action Recognition from Silhouette Images | cs.CV | In this paper, a novel human action recognition technique from video is
presented. Any action of human is a combination of several micro action
sequences performed by one or more body parts of the human. The proposed
approach uses spatio-temporal body parts movement (STBPM) features extracted
from foreground silhouette... | computer science |
25,595 | DeepProposal: Hunting Objects by Cascading Deep Convolutional Layers | cs.CV | In this paper we evaluate the quality of the activation layers of a
convolutional neural network (CNN) for the gen- eration of object proposals. We
generate hypotheses in a sliding-window fashion over different activation
layers and show that the final convolutional layers can find the object of
interest with high reca... | computer science |
25,596 | Sparsity-aware Possibilistic Clustering Algorithms | cs.CV | In this paper two novel possibilistic clustering algorithms are presented,
which utilize the concept of sparsity. The first one, called sparse
possibilistic c-means, exploits sparsity and can deal well with closely located
clusters that may also be of significantly different densities. The second one,
called sparse ada... | computer science |
25,597 | Beyond Spatial Pyramid Matching: Space-time Extended Descriptor for
Action Recognition | cs.CV | We address the problem of generating video features for action recognition.
The spatial pyramid and its variants have been very popular feature models due
to their success in balancing spatial location encoding and spatial invariance.
Although it seems straightforward to extend spatial pyramid to the temporal
domain (s... | computer science |
25,598 | A Brief Survey of Image Processing Algorithms in Electrical Capacitance
Tomography | cs.CV | To study the fundamental physics of complex multiphase flow systems using
advanced measurement techniques, especially the electrical capacitance
tomography (ECT) approach, this article carries out an initial literature
review of the ECT method from a point of view of signal processing and
algorithm design. After introd... | computer science |
25,599 | A Picture is Worth a Billion Bits: Real-Time Image Reconstruction from
Dense Binary Pixels | cs.CV | The pursuit of smaller pixel sizes at ever increasing resolution in digital
image sensors is mainly driven by the stringent price and form-factor
requirements of sensors and optics in the cellular phone market. Recently, Eric
Fossum proposed a novel concept of an image sensor with dense sub-diffraction
limit one-bit pi... | computer science |
25,600 | Shape Complexes in Continuous Max-Flow Hierarchical Multi-Labeling
Problems | cs.CV | Although topological considerations amongst multiple labels have been
previously investigated in the context of continuous max-flow image
segmentation, similar investigations have yet to be made about shape
considerations in a general and extendable manner. This paper presents shape
complexes for segmentation, which ca... | computer science |
25,601 | Multiresolution hierarchy co-clustering for semantic segmentation in
sequences with small variations | cs.CV | This paper presents a co-clustering technique that, given a collection of
images and their hierarchies, clusters nodes from these hierarchies to obtain a
coherent multiresolution representation of the image collection. We formalize
the co-clustering as a Quadratic Semi-Assignment Problem and solve it with a
linear prog... | computer science |
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