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29,802 | Using Deep Convolutional Networks for Gesture Recognition in American
Sign Language | cs.CV | In the realm of multimodal communication, sign language is, and continues to
be, one of the most understudied areas. In line with recent advances in the
field of deep learning, there are far reaching implications and applications
that neural networks can have for sign language interpretation. In this paper,
we present ... | computer science |
29,803 | Material Classification using Neural Networks | cs.CV | The recognition and classification of the diversity of materials that exist
in the environment around us are a key visual competence that computer vision
systems focus on in recent years. Understanding the identification of materials
in distinct images involves a deep process that has made usage of the recent
progress ... | computer science |
29,804 | VisDA: The Visual Domain Adaptation Challenge | cs.CV | We present the 2017 Visual Domain Adaptation (VisDA) dataset and challenge, a
large-scale testbed for unsupervised domain adaptation across visual domains.
Unsupervised domain adaptation aims to solve the real-world problem of domain
shift, where machine learning models trained on one domain must be transferred
and ada... | computer science |
29,805 | Improved Search in Hamming Space using Deep Multi-Index Hashing | cs.CV | Similarity-preserving hashing is a widely-used method for nearest neighbour
search in large-scale image retrieval tasks. There has been considerable
research on generating efficient image representation via the
deep-network-based hashing methods. However, the issue of efficient searching
in the deep representation spac... | computer science |
29,806 | Generative Adversarial Networks: An Overview | cs.CV | Generative adversarial networks (GANs) provide a way to learn deep
representations without extensively annotated training data. They achieve this
through deriving backpropagation signals through a competitive process
involving a pair of networks. The representations that can be learned by GANs
may be used in a variety ... | computer science |
29,807 | Emerging from Water: Underwater Image Color Correction Based on Weakly
Supervised Color Transfer | cs.CV | Underwater vision suffers from severe effects due to selective attenuation
and scattering when light propagates through water. Such degradation not only
affects the quality of underwater images but limits the ability of vision
tasks. Different from existing methods which either ignore the wavelength
dependency of the a... | computer science |
29,808 | Deep Self-taught Learning for Remote Sensing Image Classification | cs.CV | This paper addresses the land cover classification task for remote sensing
images by deep self-taught learning. Our self-taught learning approach learns
suitable feature representations of the input data using sparse representation
and undercomplete dictionary learning. We propose a deep learning framework
which extrac... | computer science |
29,809 | Sea Level Anomaly Prediction using Recurrent Neural Networks | cs.CV | Sea level change, one of the most dire impacts of anthropogenic global
warming, will affect a large amount of the world's population. However, sea
level change is not uniform in time and space, and the skill of conventional
prediction methods is limited due to the ocean's internal variabi-lity on
timescales from weeks ... | computer science |
29,810 | Nonlinear Supervised Dimensionality Reduction via Smooth Regular
Embeddings | cs.CV | The recovery of the intrinsic geometric structures of data collections is an
important problem in data analysis. Supervised extensions of several manifold
learning approaches have been proposed in the recent years. Meanwhile, existing
methods primarily focus on the embedding of the training data, and the
generalization... | computer science |
29,811 | Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem
GMM-HMM System | cs.CV | Automatic visual speech recognition is an interesting problem in pattern
recognition especially when audio data is noisy or not readily available. It is
also a very challenging task mainly because of the lower amount of information
in the visual articulations compared to the audible utterance. In this work,
principle c... | computer science |
29,812 | Combining Multiple Views for Visual Speech Recognition | cs.CV | Visual speech recognition is a challenging research problem with a particular
practical application of aiding audio speech recognition in noisy scenarios.
Multiple camera setups can be beneficial for the visual speech recognition
systems in terms of improved performance and robustness. In this paper, we
explore this as... | computer science |
29,813 | Block DCT filtering using vector processing | cs.CV | Filtering is an important issue in signals and images processing. Many images
and videos are compressed using discrete cosine transform (DCT). For reducing
the computation complexity, we are interested in filtering block and images
directly in DCT domain. This article proposed an efficient and yet very simple
filtering... | computer science |
29,814 | Dress like a Star: Retrieving Fashion Products from Videos | cs.CV | This work proposes a system for retrieving clothing and fashion products from
video content. Although films and television are the perfect showcase for
fashion brands to promote their products, spectators are not always aware of
where to buy the latest trends they see on screen. Here, a framework for
breaking the gap b... | computer science |
29,815 | FigureQA: An Annotated Figure Dataset for Visual Reasoning | cs.CV | We introduce FigureQA, a visual reasoning corpus of over one million
question-answer pairs grounded in over 100,000 images. The images are
synthetic, scientific-style figures from five classes: line plots, dot-line
plots, vertical and horizontal bar graphs, and pie charts. We formulate our
reasoning task by generating ... | computer science |
29,816 | Interpretable Transformations with Encoder-Decoder Networks | cs.CV | Deep feature spaces have the capacity to encode complex transformations of
their input data. However, understanding the relative feature-space
relationship between two transformed encoded images is difficult. For instance,
what is the relative feature space relationship between two rotated images?
What is decoded when ... | computer science |
29,817 | Be Your Own Prada: Fashion Synthesis with Structural Coherence | cs.CV | We present a novel and effective approach for generating new clothing on a
wearer through generative adversarial learning. Given an input image of a
person and a sentence describing a different outfit, our model "redresses" the
person as desired, while at the same time keeping the wearer and her/his pose
unchanged. Gen... | computer science |
29,818 | Historical Document Image Segmentation with LDA-Initialized Deep Neural
Networks | cs.CV | In this paper, we present a novel approach to perform deep neural networks
layer-wise weight initialization using Linear Discriminant Analysis (LDA).
Typically, the weights of a deep neural network are initialized with: random
values, greedy layer-wise pre-training (usually as Deep Belief Network or as
auto-encoder) or... | computer science |
29,819 | SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time
Road-Object Segmentation from 3D LiDAR Point Cloud | cs.CV | In this paper, we address semantic segmentation of road-objects from 3D LiDAR
point clouds. In particular, we wish to detect and categorize instances of
interest, such as cars, pedestrians and cyclists. We formulate this problem as
a point- wise classification problem, and propose an end-to-end pipeline called
SqueezeS... | computer science |
29,820 | Superpixel Based Segmentation and Classification of Polyps in Wireless
Capsule Endoscopy | cs.CV | Wireless Capsule Endoscopy (WCE) is a relatively new technology to record the
entire GI trace, in vivo. The large amounts of frames captured during an
examination cause difficulties for physicians to review all these frames. The
need for reducing the reviewing time using some intelligent methods has been a
challenge. P... | computer science |
29,821 | Light-weight place recognition and loop detection using road markings | cs.CV | In this paper, we propose an efficient algorithm for robust place recognition
and loop detection using camera information only. Our pipeline purely relies on
spatial localization and semantic information of road markings. The creation of
the database of road markings sequences is performed online, which makes the
metho... | computer science |
29,822 | Generalized Zero-Shot Learning for Action Recognition with Web-Scale
Video Data | cs.CV | Action recognition in surveillance video makes our life safer by detecting
the criminal events or predicting violent emergencies. However, efficient
action recognition is not free of difficulty. First, there are so many action
classes in daily life that we cannot pre-define all possible action classes
beforehand. Moreo... | computer science |
29,823 | Anticipating Daily Intention using On-Wrist Motion Triggered Sensing | cs.CV | Anticipating human intention by observing one's actions has many
applications. For instance, picking up a cellphone, then a charger (actions)
implies that one wants to charge the cellphone (intention). By anticipating the
intention, an intelligent system can guide the user to the closest power
outlet. We propose an on-... | computer science |
29,824 | MR to X-Ray Projection Image Synthesis | cs.CV | Hybrid imaging promises large potential in medical imaging applications. To
fully utilize the possibilities of corresponding information from different
modalities, the information must be transferable between the domains. In
radiation therapy, existing methods make use of reconstructed magnetic
resonance imaging data t... | computer science |
29,825 | SEGCloud: Semantic Segmentation of 3D Point Clouds | cs.CV | 3D semantic scene labeling is fundamental to agents operating in the real
world. In particular, labeling raw 3D point sets from sensors provides
fine-grained semantics. Recent works leverage the capabilities of Neural
Networks (NNs), but are limited to coarse voxel predictions and do not
explicitly enforce global consi... | computer science |
29,826 | Employing Fusion of Learned and Handcrafted Features for Unconstrained
Ear Recognition | cs.CV | We present an unconstrained ear recognition framework that outperforms
state-of-the-art systems in different publicly available image databases. To
this end, we developed CNN-based solutions for ear normalization and
description, we used well-known handcrafted descriptors, and we fused learned
and handcrafted features ... | computer science |
29,827 | Generalized linear mixing model accounting for endmember variability | cs.CV | Endmember variability is an important factor for accurately unveiling vital
information relating the pure materials and their distribution in hyperspectral
images. Recently, the extended linear mixing model (ELMM) has been proposed as
a modification of the linear mixing model (LMM) to consider endmember
variability eff... | computer science |
29,828 | An efficient deep learning hashing neural network for mobile visual
search | cs.CV | Mobile visual search applications are emerging that enable users to sense
their surroundings with smart phones. However, because of the particular
challenges of mobile visual search, achieving a high recognition bitrate has
becomes a consistent target of previous related works. In this paper, we
propose a few-parameter... | computer science |
29,829 | Image Disguise based on Generative Model | cs.CV | To protect image contents, most existing encryption algorithms are designed
to transform an original image into a texture-like or noise-like image, which
is, however, an obvious visual sign indicating the presence of an encrypted
image, results in a significantly large number of attacks. To solve this
problem, in this ... | computer science |
29,830 | Feature-Guided Black-Box Safety Testing of Deep Neural Networks | cs.CV | Despite the improved accuracy of deep neural networks, the discovery of
adversarial examples has raised serious safety concerns. Most existing
approaches for crafting adversarial examples necessitate some knowledge
(architecture, parameters, etc.) of the network at hand. In this paper, we
focus on image classifiers and... | computer science |
29,831 | Backtracking Regression Forests for Accurate Camera Relocalization | cs.CV | Camera relocalization plays a vital role in many robotics and computer vision
tasks, such as global localization, recovery from tracking failure, and loop
closure detection. Recent random forests based methods directly predict 3D
world locations for 2D image locations to guide the camera pose optimization.
During train... | computer science |
29,832 | ActivityNet Challenge 2017 Summary | cs.CV | The ActivityNet Large Scale Activity Recognition Challenge 2017 Summary:
results and challenge participants papers. | computer science |
29,833 | Deep Cropping via Attention Box Prediction and Aesthetics Assessment | cs.CV | We model the photo cropping problem as a cascade of attention box regression
and aesthetic quality classification, based on deep learning. A neural network
is designed that has two branches for predicting attention bounding box and
analyzing aesthetics, respectively. The predicted attention box is treated as
an initial... | computer science |
29,834 | Feedback-prop: Convolutional Neural Network Inference under Partial
Evidence | cs.CV | In this paper, we propose an inference procedure for deep convolutional
neural networks (CNNs) where partial evidence might be available during
inference. We introduce a general feedback-based propagation approach
(feedback-prop) that allows us to boost the prediction accuracy of an existing
CNN model for an arbitrary ... | computer science |
29,835 | VGGFace2: A dataset for recognising faces across pose and age | cs.CV | In this paper, we introduce a new large-scale face dataset named VGGFace2.
The dataset contains 3.31 million images of 9131 subjects, with an average of
362.6 images for each subject. Images are downloaded from Google Image Search
and have large variations in pose, age, illumination, ethnicity and profession
(e.g. acto... | computer science |
29,836 | Accelerating GMM-based patch priors for image restoration: Three
ingredients for a 100$\times$ speed-up | cs.CV | Image restoration methods aim to recover the underlying clean image from
corrupted observations. The Expected Patch Log-likelihood (EPLL) algorithm is a
powerful image restoration method that uses a Gaussian mixture model (GMM)
prior on the patches of natural images. Although it is very effective for
restoring images, ... | computer science |
29,837 | An iterative closest point method for measuring the level of similarity
of 3d log scans in wood industry | cs.CV | In the Canadian's lumber industry, simulators are used to predict the lumbers
resulting from the sawing of a log at a given sawmill. Giving a log or several
logs' 3D scans as input, simulators perform a real-time job to predict the
lumbers. These simulators, however, tend to be slow at processing large volume
of wood. ... | computer science |
29,838 | An In-field Automatic Wheat Disease Diagnosis System | cs.CV | Crop diseases are responsible for the major production reduction and economic
losses in agricultural industry world- wide. Monitoring for health status of
crops is critical to control the spread of diseases and implement effective
management. This paper presents an in-field automatic wheat disease diagnosis
system base... | computer science |
29,839 | Fully Context-Aware Video Prediction | cs.CV | This paper proposes a new neural network design for unsupervised learning
through video prediction. Current video prediction models based on
convolutional networks, recurrent networks, and their combinations often result
in blurry predictions. Recent work has attempted to address this issue with
techniques like separat... | computer science |
29,840 | The Shape of an Image: A Study of Mapper on Images | cs.CV | We study the topological construction called Mapper in the context of simply
connected domains, in particular on images. The Mapper construction can be
considered as a generalization for contour, split, and joint trees on simply
connected domains. A contour tree on an image domain assumes the height
function to be a pi... | computer science |
29,841 | Human-level CMR image analysis with deep fully convolutional networks | cs.CV | Cardiovascular magnetic resonance (CMR) imaging is a standard imaging
modality for assessing cardiovascular diseases (CVDs), the leading cause of
death globally. CMR enables accurate quantification of the cardiac chamber
volume, ejection fraction and myocardial mass, providing a wealth of
information for sensitive and ... | computer science |
29,842 | LOOP Descriptor: Local Optimal Oriented Pattern | cs.CV | This letter introduces the LOOP binary descriptor (local optimal oriented
pattern) that encodes rotation invariance into the main formulation itself.
This makes any post processing stage for rotation invariance redundant and
improves on both accuracy and time complexity. We consider fine-grained
lepidoptera (moth/butte... | computer science |
29,843 | Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning | cs.CV | Brain segmentation is a fundamental first step in neuroimage analysis. In the
case of fetal MRI, it is particularly challenging and important due to the
arbitrary orientation of the fetus, organs that surround the fetal head, and
intermittent fetal motion. Several promising methods have been proposed but are
limited in... | computer science |
29,844 | High Five: Improving Gesture Recognition by Embracing Uncertainty | cs.CV | Sensors on mobile devices---accelerometers, gyroscopes, pressure meters, and
GPS---invite new applications in gesture recognition, gaming, and fitness
tracking. However, programming them remains challenging because human gestures
captured by sensors are noisy. This paper illustrates that noisy gestures
degrade training... | computer science |
29,845 | Complete 3D Scene Parsing from Single RGBD Image | cs.CV | Inferring the location, shape, and class of each object in a single image is
an important task in computer vision. In this paper, we aim to predict the full
3D parse of both visible and occluded portions of the scene from one RGBD
image. We parse the scene by modeling objects as detailed CAD models with class
labels an... | computer science |
29,846 | Knowledge Projection for Deep Neural Networks | cs.CV | While deeper and wider neural networks are actively pushing the performance
limits of various computer vision and machine learning tasks, they often
require large sets of labeled data for effective training and suffer from
extremely high computational complexity. In this paper, we will develop a new
framework for train... | computer science |
29,847 | Artifact reduction for separable non-local means | cs.CV | It was recently demonstrated [J. Electron. Imaging, 25(2), 2016] that one can
perform fast non-local means (NLM) denoising of one-dimensional signals using a
method called lifting. The cost of lifting is independent of the patch length,
which dramatically reduces the run-time for large patches. Unfortunately, it is
dif... | computer science |
29,848 | Improved Workflow for Unsupervised Multiphase Image Segmentation | cs.CV | Quantitative image analysis often depends on accurate classification of
pixels through a segmentation process. However, imaging artifacts such as the
partial volume effect and sensor noise complicate the classification process.
These effects increase the pixel intensity variance of each constituent class,
causing inten... | computer science |
29,849 | Class Correlation affects Single Object Localization using Pre-trained
ConvNets | cs.CV | The problem of object localization has become one of the mainstream problems
of vision. Most of the algorithms proposed involve the design for the model to
be specifically for localizing objects. In this paper, we explore whether a
pre-trained canonical ConvNet (without fine-tuning) trained purely for object
classifica... | computer science |
29,850 | Deep Spatial Regression Model for Image Crowd Counting | cs.CV | Computer vision techniques have been used to produce accurate and generic
crowd count estimators in recent years. Due to severe occlusions, appearance
variations, perspective distortions and illumination conditions, crowd counting
is a very challenging task. To this end, we propose a deep spatial regression
model(DSRM)... | computer science |
29,851 | Spiking Optical Flow for Event-based Sensors Using IBM's TrueNorth
Neurosynaptic System | cs.CV | This paper describes a fully spike-based neural network for optical flow
estimation from Dynamic Vision Sensor data. A low power embedded implementation
of the method which combines the Asynchronous Time-based Image Sensor with
IBM's TrueNorth Neurosynaptic System is presented. The sensor generates spikes
with sub-mill... | computer science |
29,852 | Dynamic Routing Between Capsules | cs.CV | A capsule is a group of neurons whose activity vector represents the
instantiation parameters of a specific type of entity such as an object or an
object part. We use the length of the activity vector to represent the
probability that the entity exists and its orientation to represent the
instantiation parameters. Acti... | computer science |
29,853 | How far did we get in face spoofing detection? | cs.CV | The growing use of control access systems based on face recognition shed
light over the need for even more accurate systems to detect face spoofing
attacks. In this paper, an extensive analysis on face spoofing detection works
published in the last decade is presented. The analyzed works are categorized
by their fundam... | computer science |
29,854 | Image Compression: Sparse Coding vs. Bottleneck Autoencoders | cs.CV | Bottleneck autoencoders have been actively researched as a solution to image
compression tasks. However, we observed that bottleneck autoencoders produce
subjectively low quality reconstructed images. In this work, we explore the
ability of sparse coding to improve reconstructed image quality for the same
degree of com... | computer science |
29,855 | SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D
images used in the Shoot Apical Meristem | cs.CV | The quantitative analysis of 3D confocal microscopy images of the shoot
apical meristem helps understanding the growth process of some plants. Cell
segmentation in these images is crucial for computational plant analysis and
many automated methods have been proposed. However, variations in signal
intensity across the i... | computer science |
29,856 | PoseTrack: A Benchmark for Human Pose Estimation and Tracking | cs.CV | Human poses and motions are important cues for analysis of videos with people
and there is strong evidence that representations based on body pose are highly
effective for a variety of tasks such as activity recognition, content
retrieval and social signal processing. In this work, we aim to further advance
the state o... | computer science |
29,857 | Deterministic Approximate Methods for Maximum Consensus Robust Fitting | cs.CV | Maximum consensus estimation plays a critically important role in robust
fitting problems in computer vision. Currently, the most prevalent algorithms
for consensus maximization draw from the class of randomized
hypothesize-and-verify algorithms, which are cheap but can usually deliver only
rough approximate solutions.... | computer science |
29,858 | SceneFlowFields: Dense Interpolation of Sparse Scene Flow
Correspondences | cs.CV | While most scene flow methods use either variational optimization or a strong
rigid motion assumption, we show for the first time that scene flow can also be
estimated by dense interpolation of sparse matches. To this end, we find sparse
matches across two stereo image pairs that are detected without any prior
regulari... | computer science |
29,859 | Image matting with normalized weight and semi-supervised learning | cs.CV | Image matting is an important vision problem. The main stream methods for it
combine sampling-based methods and propagation-based methods. In this paper, we
deal with the combination with a normalized weighting parameter, which could
well control the relative relationship between information from sampling and
from prop... | computer science |
29,860 | High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial
Networks | cs.CV | Synthesizing face sketches from real photos and its inverse have many
applications. However, photo/sketch synthesis remains a challenging problem due
to the fact that photo and sketch have different characteristics. In this work,
we consider this task as an image-to-image translation problem and explore the
recently po... | computer science |
29,861 | Enhanced Biologically Inspired Model for Image Recognition Based on a
Novel Patch Selection Method with Moment | cs.CV | Biologically inspired model (BIM) for image recognition is a robust
computational architecture, which has attracted widespread attention. BIM can
be described as a four-layer structure based on the mechanisms of the visual
cortex. Although the performance of BIM for image recognition is robust, it
takes the randomly se... | computer science |
29,862 | Dual Path Networks for Multi-Person Human Pose Estimation | cs.CV | The task of multi-person human pose estimation in natural scenes is quite
challenging. Existing methods include both top-down and bottom-up approaches.
The main advantage of bottom-up methods is its excellent tradeoff between
estimation accuracy and computational cost. We follow this path and aim to
design smaller, fas... | computer science |
29,863 | Detection and Analysis of Human Emotions through Voice and Speech
Pattern Processing | cs.CV | The ability to modulate vocal sounds and generate speech is one of the
features which set humans apart from other living beings. The human voice can
be characterized by several attributes such as pitch, timbre, loudness, and
vocal tone. It has often been observed that humans express their emotions by
varying different ... | computer science |
29,864 | Multi-modal Aggregation for Video Classification | cs.CV | In this paper, we present a solution to Large-Scale Video Classification
Challenge (LSVC2017) [1] that ranked the 1st place. We focused on a variety of
modalities that cover visual, motion and audio. Also, we visualized the
aggregation process to better understand how each modality takes effect. Among
the extracted mod... | computer science |
29,865 | Total-Text: A Comprehensive Dataset for Scene Text Detection and
Recognition | cs.CV | Text in curve orientation, despite being one of the common text orientations
in real world environment, has close to zero existence in well received scene
text datasets such as ICDAR2013 and MSRA-TD500. The main motivation of
Total-Text is to fill this gap and facilitate a new research direction for the
scene text comm... | computer science |
29,866 | SeeThrough: Finding Chairs in Heavily Occluded Indoor Scene Images | cs.CV | Discovering 3D arrangements of objects from single indoor images is important
given its many applications including interior design, content creation, etc.
Although heavily researched in the recent years, existing approaches break down
under medium or heavy occlusion as the core object detection module starts
failing i... | computer science |
29,867 | Learning to diagnose from scratch by exploiting dependencies among
labels | cs.CV | The field of medical diagnostics contains a wealth of challenges which
closely resemble classical machine learning problems; practical constraints,
however, complicate the translation of these endpoints naively into classical
architectures. Many tasks in radiology, for example, are largely problems of
multi-label class... | computer science |
29,868 | Object Recognition by Using Multi-level Feature Point Extraction | cs.CV | In this paper, we present a novel approach for object recognition in
real-time by employing multilevel feature analysis and demonstrate the
practicality of adapting feature extraction into a Naive Bayesian
classification framework that enables simple, efficient, and robust
performance. We also show the proposed method ... | computer science |
29,869 | A Novel Approach to Artistic Textual Visualization via GAN | cs.CV | While the visualization of statistical data tends to a mature technology, the
visualization of textual data is still in its infancy, especially for the
artistic text. Due to the fact that visualization of artistic text is valuable
and attractive in both art and information science, we attempt to realize this
tentative ... | computer science |
29,870 | Synthetic Iris Presentation Attack using iDCGAN | cs.CV | Reliability and accuracy of iris biometric modality has prompted its
large-scale deployment for critical applications such as border control and
national ID projects. The extensive growth of iris recognition systems has
raised apprehensions about susceptibility of these systems to various attacks.
In the past, research... | computer science |
29,871 | Examining CNN Representations with respect to Dataset Bias | cs.CV | Given a pre-trained CNN without any testing samples, this paper proposes a
simple yet effective method to diagnose feature representations of the CNN. We
aim to discover representation flaws caused by potential dataset bias. More
specifically, when the CNN is trained to estimate image attributes, we mine
latent relatio... | computer science |
29,872 | Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep
Learning-Based Approach | cs.CV | Knee osteoarthritis (OA) is the most common musculoskeletal disorder. OA
diagnosis is currently conducted by assessing symptoms and evaluating plain
radiographs, but this process suffers from subjectivity. In this study, we
present a new transparent computer-aided diagnosis method based on the Deep
Siamese Convolutiona... | computer science |
29,873 | A Study on Topological Descriptors for the Analysis of 3D Surface
Texture | cs.CV | Methods from computational topology are becoming more and more popular in
computer vision and have shown to improve the state-of-the-art in several
tasks. In this paper, we investigate the applicability of topological
descriptors in the context of 3D surface analysis for the classification of
different surface textures... | computer science |
29,874 | High-Precision Localization Using Ground Texture | cs.CV | Location-aware applications play an increasingly critical role in everyday
life. However, the most common global localization technology - GPS - has
limited accuracy and can be unusable in dense urban areas and indoors. We
introduce an image-based global localization system that is accurate to a few
millimeters and per... | computer science |
29,875 | Multilinear Class-Specific Discriminant Analysis | cs.CV | There has been a great effort to transfer linear discriminant techniques that
operate on vector data to high-order data, generally referred to as Multilinear
Discriminant Analysis (MDA) techniques. Many existing works focus on maximizing
the inter-class variances to intra-class variances defined on tensor data
represen... | computer science |
29,876 | On Pre-Trained Image Features and Synthetic Images for Deep Learning | cs.CV | Deep Learning methods usually require huge amounts of training data to
perform at their full potential, and often require expensive manual labeling.
Using synthetic images is therefore very attractive to train object detectors,
as the labeling comes for free, and several approaches have been proposed to
combine synthet... | computer science |
29,877 | A Saak Transform Approach to Efficient, Scalable and Robust Handwritten
Digits Recognition | cs.CV | An efficient, scalable and robust approach to the handwritten digits
recognition problem based on the Saak transform is proposed in this work.
First, multi-stage Saak transforms are used to extract a family of joint
spatial-spectral representations of input images. Then, the Saak coefficients
are used as features and f... | computer science |
29,878 | Can you find a face in a HEVC bitstream? | cs.CV | Finding faces in images is one of the most important tasks in computer
vision, with applications in biometrics, surveillance, human-computer
interaction, and other areas. In our earlier work, we demonstrated that it is
possible to tell whether or not an image contains a face by only examining the
HEVC syntax, without f... | computer science |
29,879 | Cascade Region Proposal and Global Context for Deep Object Detection | cs.CV | Deep region-based object detector consists of a region proposal step and a
deep object recognition step. In this paper, we make significant improvements
on both of the two steps. For region proposal we propose a novel lightweight
cascade structure which can effectively improve RPN proposal quality. For
object recogniti... | computer science |
29,880 | DART: Distribution Aware Retinal Transform for Event-based Cameras | cs.CV | We introduce a new event-based visual descriptor, termed as distribution
aware retinal transform (DART), for pattern recognition using silicon retina
cameras. The DART descriptor captures the information of the spatio-temporal
distribution of events, and forms a rich structural representation.
Consequently, the event c... | computer science |
29,881 | Open Set Logo Detection and Retrieval | cs.CV | Current logo retrieval research focuses on closed set scenarios. We argue
that the logo domain is too large for this strategy and requires an open set
approach. To foster research in this direction, a large-scale logo dataset,
called Logos in the Wild, is collected and released to the public. A typical
open set logo re... | computer science |
29,882 | Grad-CAM++: Generalized Gradient-based Visual Explanations for Deep
Convolutional Networks | cs.CV | Over the last decade, Convolutional Neural Network (CNN) models have been
highly successful in solving complex vision based problems. However, deep
models are perceived as "black box" methods considering the lack of
understanding of their internal functioning. There has been a significant
recent interest to develop exp... | computer science |
29,883 | Continuous Authentication Using One-class Classifiers and their Fusion | cs.CV | While developing continuous authentication systems (CAS), we generally assume
that samples from both genuine and impostor classes are readily available.
However, the assumption may not be true in certain circumstances. Therefore, we
explore the possibility of implementing CAS using only genuine samples.
Specifically, w... | computer science |
29,884 | An Integrated Approach to Crowd Video Analysis: From Tracking to
Multi-level Activity Recognition | cs.CV | We present an integrated framework for simultaneous tracking, group detection
and multi-level activity recognition in crowd videos. Instead of solving these
problems independently and sequentially, we solve them together in a unified
framework to utilize the strong correlation that exists among individual
motion, group... | computer science |
29,885 | Automated Tumor Segmentation and Brain Mapping for the Tumor Area | cs.CV | Magnetic Resonance Imaging (MRI) is an important diagnostic tool for precise
detection of various pathologies. Magnetic Resonance (MR) is more preferred
than Computed Tomography (CT) due to the high resolution in MR images which
help in better detection of neurological conditions. Graphical user interface
(GUI) aided d... | computer science |
29,886 | Deep word embeddings for visual speech recognition | cs.CV | In this paper we present a deep learning architecture for extracting word
embeddings for visual speech recognition. The embeddings summarize the
information of the mouth region that is relevant to the problem of word
recognition, while suppressing other types of variability such as speaker, pose
and illumination. The s... | computer science |
29,887 | Deep Learning and Conditional Random Fields-based Depth Estimation and
Topographical Reconstruction from Conventional Endoscopy | cs.CV | Colorectal cancer is the fourth leading cause of cancer deaths worldwide and
the second leading cause in the United States. The risk of colorectal cancer
can be mitigated by the identification and removal of premalignant lesions
through optical colonoscopy. Unfortunately, conventional colonoscopy misses
more than 20% o... | computer science |
29,888 | Tumor Classification and Segmentation of MR Brain Images | cs.CV | The diagnosis and segmentation of tumors using any medical diagnostic tool
can be challenging due to the varying nature of this pathology. Magnetic Reso-
nance Imaging (MRI) is an established diagnostic tool for various diseases and
disorders and plays a major role in clinical neuro-diagnosis. Supplementing
this techni... | computer science |
29,889 | Spatio-temporal interaction model for crowd video analysis | cs.CV | We present an unsupervised approach to analyze crowd at various levels of
granularity $-$ individual, group and collective. We also propose a motion
model to represent the collective motion of the crowd. The model captures the
spatio-temporal interaction pattern of the crowd from the trajectory data
captured over a tim... | computer science |
29,890 | Image Patch Matching Using Convolutional Descriptors with Euclidean
Distance | cs.CV | In this work we propose a neural network based image descriptor suitable for
image patch matching, which is an important task in many computer vision
applications. Our approach is influenced by recent success of deep
convolutional neural networks (CNNs) in object detection and classification
tasks. We develop a model w... | computer science |
29,891 | A Computer Vision System to Localize and Classify Wastes on the Streets | cs.CV | Littering quantification is an important step for improving cleanliness of
cities. When human interpretation is too cumbersome or in some cases
impossible, an objective index of cleanliness could reduce the littering by
awareness actions. In this paper, we present a fully automated computer vision
application for litte... | computer science |
29,892 | Deep Hashing with Triplet Quantization Loss | cs.CV | With the explosive growth of image databases, deep hashing, which learns
compact binary descriptors for images, has become critical for fast image
retrieval. Many existing deep hashing methods leverage quantization loss,
defined as distance between the features before and after quantization, to
reduce the error from bi... | computer science |
29,893 | Clothing Retrieval with Visual Attention Model | cs.CV | Clothing retrieval is a challenging problem in computer vision. With the
advance of Convolutional Neural Networks (CNNs), the accuracy of clothing
retrieval has been significantly improved. FashionNet[1], a recent study,
proposes to employ a set of artificial features in the form of landmarks for
clothing retrieval, wh... | computer science |
29,894 | Multiple Instance Hybrid Estimator for Hyperspectral Target
Characterization and Sub-pixel Target Detection | cs.CV | The Multiple Instance Hybrid Estimator for discriminative target
characterization from imprecisely labeled hyperspectral data is presented. In
many hyperspectral target detection problems, acquiring accurately labeled
training data is difficult. Furthermore, each pixel containing target is likely
to be a mixture of bot... | computer science |
29,895 | Common Representation Learning Using Step-based Correlation Multi-Modal
CNN | cs.CV | Deep learning techniques have been successfully used in learning a common
representation for multi-view data, wherein the different modalities are
projected onto a common subspace. In a broader perspective, the techniques used
to investigate common representation learning falls under the categories of
canonical correla... | computer science |
29,896 | Semantic Image Retrieval via Active Grounding of Visual Situations | cs.CV | We describe a novel architecture for semantic image retrieval---in
particular, retrieval of instances of visual situations. Visual situations are
concepts such as "a boxing match," "walking the dog," "a crowd waiting for a
bus," or "a game of ping-pong," whose instantiations in images are linked more
by their common sp... | computer science |
29,897 | Multi-Task Learning by Deep Collaboration and Application in Facial
Landmark Detection | cs.CV | Convolutional neural networks (CNNs) have become the most successful approach
in many vision-related domains. However, they are limited to domains where data
is abundant. Recent works have looked at multi-task learning (MTL) to mitigate
data scarcity by leveraging domain-specific information from related tasks. In
this... | computer science |
29,898 | PupilNet v2.0: Convolutional Neural Networks for CPU based real time
Robust Pupil Detection | cs.CV | Real-time, accurate, and robust pupil detection is an essential prerequisite
for pervasive video-based eye-tracking. However, automated pupil detection in
realworld scenarios has proven to be an intricate challenge due to fast
illumination changes, pupil occlusion, non-centered and off-axis eye recording,
as well as ph... | computer science |
29,899 | Countering Adversarial Images using Input Transformations | cs.CV | This paper investigates strategies that defend against adversarial-example
attacks on image-classification systems by transforming the inputs before
feeding them to the system. Specifically, we study applying image
transformations such as bit-depth reduction, JPEG compression, total variance
minimization, and image qui... | computer science |
29,900 | Segmentation-by-Detection: A Cascade Network for Volumetric Medical
Image Segmentation | cs.CV | We propose an attention mechanism for 3D medical image segmentation. The
method, named segmentation-by-detection, is a cascade of a detection module
followed by a segmentation module. The detection module enables a region of
interest to come to attention and produces a set of object region candidates
which are further ... | computer science |
29,901 | Improving Object Localization with Fitness NMS and Bounded IoU Loss | cs.CV | We demonstrate that many detection methods are designed to identify only a
sufficently accurate bounding box, rather than the best available one. To
address this issue we propose a simple and fast modification to the existing
methods called Fitness NMS. This method is tested with the DeNet model and
obtains a significa... | computer science |
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