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29,502 | Kernel Cross-Correlator | cs.CV | Cross-correlator plays a significant role in many visual perception tasks,
such as object detection and tracking. Beyond the linear cross-correlator, this
paper proposes a kernel cross-correlator (KCC) that breaks traditional
limitations. First, by introducing the kernel trick, the KCC extends the linear
cross-correlat... | computer science |
29,503 | Normal Integration: A Survey | cs.CV | The need for efficient normal integration methods is driven by several
computer vision tasks such as shape-from-shading, photometric stereo,
deflectometry, etc. In the first part of this survey, we select the most
important properties that one may expect from a normal integration method,
based on a thorough study of tw... | computer science |
29,504 | Towards a Crowd Analytic Framework For Crowd Management in
Majid-al-Haram | cs.CV | The scared cities of Makkah Al Mukarramah and Madina Al Munawarah host
millions of pilgrims every year. During Hajj, the movement of large number of
people has a unique spatial and temporal constraints, which makes Hajj one of
toughest challenges for crowd management. In this paper, we propose a computer
vision based f... | computer science |
29,505 | Adaptive compressed 3D imaging based on wavelet trees and Hadamard
multiplexing with a single photon counting detector | cs.CV | Photon counting 3D imaging allows to obtain 3D images with single-photon
sensitivity and sub-ns temporal resolution. However, it is challenging to scale
to high spatial resolution. In this work, we demonstrate a photon counting 3D
imaging technique with short-pulsed structured illumination and a single-pixel
photon cou... | computer science |
29,506 | Variational Methods for Normal Integration | cs.CV | The need for an efficient method of integration of a dense normal field is
inspired by several computer vision tasks, such as shape-from-shading,
photometric stereo, deflectometry, etc. Inspired by edge-preserving methods
from image processing, we study in this paper several variational approaches
for normal integratio... | computer science |
29,507 | Multi-Person Pose Estimation via Column Generation | cs.CV | We study the problem of multi-person pose estimation in natural images. A
pose estimate describes the spatial position and identity (head, foot, knee,
etc.) of every non-occluded body part of a person. Pose estimation is difficult
due to issues such as deformation and variation in body configurations and
occlusion of p... | computer science |
29,508 | Video Object Segmentation Without Temporal Information | cs.CV | Video Object Segmentation, and video processing in general, has been
historically dominated by methods that rely on the temporal consistency and
redundancy in consecutive video frames. When the temporal smoothness is
suddenly broken, such as when an object is occluded, or some frames are missing
in a sequence, the resu... | computer science |
29,509 | Vehicle Tracking in Wide Area Motion Imagery via Stochastic Progressive
Association Across Multiple Frames (SPAAM) | cs.CV | Vehicle tracking in Wide Area Motion Imagery (WAMI) relies on associating
vehicle detections across multiple WAMI frames to form tracks corresponding to
individual vehicles. The temporal window length, i.e., the number $M$ of
sequential frames, over which associations are collectively estimated poses a
trade-off betwee... | computer science |
29,510 | Target-adaptive CNN-based pansharpening | cs.CV | We recently proposed a convolutional neural network (CNN) for remote sensing
image pansharpening obtaining a significant performance gain over the state of
the art. In this paper, we explore a number of architectural and training
variations to this baseline, achieving further performance gains with a
lightweight networ... | computer science |
29,511 | Rotation Adaptive Visual Object Tracking with Motion Consistency | cs.CV | Visual Object tracking research has undergone significant improvement in the
past few years. The emergence of tracking by detection approach in tracking
paradigm has been quite successful in many ways. Recently, deep convolutional
neural networks have been extensively used in most successful trackers. Yet,
the standard... | computer science |
29,512 | How intelligent are convolutional neural networks? | cs.CV | Motivated by the Gestalt pattern theory, and the Winograd Challenge for
language understanding, we design synthetic experiments to investigate a deep
learning algorithm's ability to infer simple (at least for human) visual
concepts, such as symmetry, from examples. A visual concept is represented by
randomly generated,... | computer science |
29,513 | Matterport3D: Learning from RGB-D Data in Indoor Environments | cs.CV | Access to large, diverse RGB-D datasets is critical for training RGB-D scene
understanding algorithms. However, existing datasets still cover only a limited
number of views or a restricted scale of spaces. In this paper, we introduce
Matterport3D, a large-scale RGB-D dataset containing 10,800 panoramic views
from 194,4... | computer science |
29,514 | A Fast Algorithm Based on a Sylvester-like Equation for LS Regression
with GMRF Prior | cs.CV | This paper presents a fast approach for penalized least squares (LS)
regression problems using a 2D Gaussian Markov random field (GMRF) prior. More
precisely, the computation of the proximity operator of the LS criterion
regularized by different GMRF potentials is formulated as solving a
Sylvester-like matrix equation.... | computer science |
29,515 | CISRDCNN: Super-resolution of compressed images using deep convolutional
neural networks | cs.CV | In recent years, much research has been conducted on image super-resolution
(SR). To the best of our knowledge, however, few SR methods were concerned with
compressed images. The SR of compressed images is a challenging task due to the
complicated compression artifacts, while many images suffer from them in
practice. T... | computer science |
29,516 | Training Better CNNs Requires to Rethink ReLU | cs.CV | With the rapid development of Deep Convolutional Neural Networks (DCNNs),
numerous works focus on designing better network architectures (i.e., AlexNet,
VGG, Inception, ResNet and DenseNet etc.). Nevertheless, all these networks
have the same characteristic: each convolutional layer is followed by an
activation layer, ... | computer science |
29,517 | Look Wider to Match Image Patches with Convolutional Neural Networks | cs.CV | When a human matches two images, the viewer has a natural tendency to view
the wide area around the target pixel to obtain clues of right correspondence.
However, designing a matching cost function that works on a large window in the
same way is difficult. The cost function is typically not intelligent enough to
discar... | computer science |
29,518 | Compressing Low Precision Deep Neural Networks Using Sparsity-Induced
Regularization in Ternary Networks | cs.CV | A low precision deep neural network training technique for producing sparse,
ternary neural networks is presented. The technique incorporates hard- ware
implementation costs during training to achieve significant model compression
for inference. Training involves three stages: network training using L2
regularization a... | computer science |
29,519 | Colour Terms: a Categorisation Model Inspired by Visual Cortex Neurons | cs.CV | Although it seems counter-intuitive, categorical colours do not exist as
external physical entities but are very much the product of our brains. Our
cortical machinery segments the world and associate objects to specific colour
terms, which is not only convenient for communication but also increases the
efficiency of v... | computer science |
29,520 | Exploring Human-like Attention Supervision in Visual Question Answering | cs.CV | Attention mechanisms have been widely applied in the Visual Question
Answering (VQA) task, as they help to focus on the area-of-interest of both
visual and textual information. To answer the questions correctly, the model
needs to selectively target different areas of an image, which suggests that an
attention-based mo... | computer science |
29,521 | Predicting Video Saliency with Object-to-Motion CNN and Two-layer
Convolutional LSTM | cs.CV | Over the past few years, deep neural networks (DNNs) have exhibited great
success in predicting the saliency of images. However, there are few works that
apply DNNs to predict the saliency of generic videos. In this paper, we propose
a novel DNN-based video saliency prediction method. Specifically, we establish
a large... | computer science |
29,522 | Fitting Generalized Essential Matrices from Generic 6x6 Matrices and its
Applications | cs.CV | This paper addresses the problem of finding the closest generalized essential
matrix from a given 6x6 matrix, with respect to the Frobenius norm. To the best
of our knowledge, this nonlinear constrained optimization problem has not been
addressed in the literature yet. Although it can be solved directly, it
involves a ... | computer science |
29,523 | 3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily
Oriented 2D Images | cs.CV | Limited capture range, and the requirement to provide high quality
initialization for optimization-based 2D/3D image registration methods, can
significantly degrade the performance of 3D image reconstruction and motion
compensation pipelines. Challenging clinical imaging scenarios, which contain
significant subject mot... | computer science |
29,524 | An Adaptive Algorithm for Precise Pupil Boundary Detection using Entropy
of Contour Gradients | cs.CV | Eye tracking spreads through a vast area of applications from ophthalmology,
assistive technologies to gaming and virtual reality. Detection of pupil is the
most critical step in many of these tasks hence needs to be performed
accurately. Although detection of pupil is a smooth task in clear sight,
possible occlusions ... | computer science |
29,525 | A General Framework for the Recognition of Online Handwritten Graphics | cs.CV | We propose a new framework for the recognition of online handwritten
graphics. Three main features of the framework are its ability to treat symbol
and structural level information in an integrated way, its flexibility with
respect to different families of graphics, and means to control the tradeoff
between recognition... | computer science |
29,526 | Human Action Forecasting by Learning Task Grammars | cs.CV | For effective human-robot interaction, it is important that a robotic
assistant can forecast the next action a human will consider in a given task.
Unfortunately, real-world tasks are often very long, complex, and repetitive;
as a result forecasting is not trivial. In this paper, we propose a novel deep
recurrent archi... | computer science |
29,527 | Automatic Leaf Extraction from Outdoor Images | cs.CV | Automatic plant recognition and disease analysis may be streamlined by an
image of a complete, isolated leaf as an initial input. Segmenting leaves from
natural images is a hard problem. Cluttered and complex backgrounds: often
composed of other leaves are commonplace. Furthermore, their appearance is
highly dependent ... | computer science |
29,528 | Human Activity Recognition Using Robust Adaptive Privileged
Probabilistic Learning | cs.CV | In this work, a novel method based on the learning using privileged
information (LUPI) paradigm for recognizing complex human activities is
proposed that handles missing information during testing. We present a
supervised probabilistic approach that integrates LUPI into a hidden
conditional random field (HCRF) model. T... | computer science |
29,529 | 3D Reconstruction with Low Resolution, Small Baseline and High Radial
Distortion Stereo Images | cs.CV | In this paper we analyze and compare approaches for 3D reconstruction from
low-resolution (250x250), high radial distortion stereo images, which are
acquired with small baseline (approximately 1mm). These images are acquired
with the system NanEye Stereo manufactured by CMOSIS/AWAIBA. These stereo
cameras have also sma... | computer science |
29,530 | Image operator learning coupled with CNN classification and its
application to staff line removal | cs.CV | Many image transformations can be modeled by image operators that are
characterized by pixel-wise local functions defined on a finite support window.
In image operator learning, these functions are estimated from training data
using machine learning techniques. Input size is usually a critical issue when
using learning... | computer science |
29,531 | Convolutional Long Short-Term Memory Networks for Recognizing First
Person Interactions | cs.CV | In this paper, we present a novel deep learning based approach for addressing
the problem of interaction recognition from a first person perspective. The
proposed approach uses a pair of convolutional neural networks, whose
parameters are shared, for extracting frame level features from successive
frames of the video. ... | computer science |
29,532 | SalNet360: Saliency Maps for omni-directional images with CNN | cs.CV | The prediction of Visual Attention data from any kind of media is of valuable
use to content creators and used to efficiently drive encoding algorithms. With
the current trend in the Virtual Reality (VR) field, adapting known techniques
to this new kind of media is starting to gain momentum. In this paper, we
present a... | computer science |
29,533 | Face Retrieval using Frequency Decoded Local Descriptor | cs.CV | The local descriptors have been the backbone of most of the computer vision
problems. Most of the existing local descriptors are generated over the raw
input images. In order to increase the discriminative power of the local
descriptors, some researchers converted the raw image into multiple images with
the help some h... | computer science |
29,534 | A LBP Based Correspondence Identification Scheme for Multi-view Sensing
Network | cs.CV | In this paper, we describes a correspondence identification method between
two-views of regular RGB camera that can be run in real-time. The basic idea is
first applying normalized cross correlation to retrieve a sparse set of
matching pairs from image pair. Then loopy belief propagation scheme is applied
to the the se... | computer science |
29,535 | Learning to Detect Violent Videos using Convolutional Long Short-Term
Memory | cs.CV | Developing a technique for the automatic analysis of surveillance videos in
order to identify the presence of violence is of broad interest. In this work,
we propose a deep neural network for the purpose of recognizing violent videos.
A convolutional neural network is used to extract frame level features from a
video. ... | computer science |
29,536 | When 3D-Aided 2D Face Recognition Meets Deep Learning: An extended UR2D
for Pose-Invariant Face Recognition | cs.CV | Most of the face recognition works focus on specific modules or demonstrate a
research idea. This paper presents a pose-invariant 3D-aided 2D face
recognition system (UR2D) that is robust to pose variations as large as 90? by
leveraging deep learning technology. The architecture and the interface of UR2D
are described,... | computer science |
29,537 | Curriculum Learning of Visual Attribute Clusters for Multi-Task
Classification | cs.CV | Visual attributes, from simple objects (e.g., backpacks, hats) to
soft-biometrics (e.g., gender, height, clothing) have proven to be a powerful
representational approach for many applications such as image description and
human identification. In this paper, we introduce a novel method to combine the
advantages of both... | computer science |
29,538 | SegFlow: Joint Learning for Video Object Segmentation and Optical Flow | cs.CV | This paper proposes an end-to-end trainable network, SegFlow, for
simultaneously predicting pixel-wise object segmentation and optical flow in
videos. The proposed SegFlow has two branches where useful information of
object segmentation and optical flow is propagated bidirectionally in a unified
framework. The segmenta... | computer science |
29,539 | Latent Embeddings for Collective Activity Recognition | cs.CV | Rather than simply recognizing the action of a person individually,
collective activity recognition aims to find out what a group of people is
acting in a collective scene. Previ- ous state-of-the-art methods using
hand-crafted potentials in conventional graphical model which can only define a
limited range of relation... | computer science |
29,540 | UnDeepVO: Monocular Visual Odometry through Unsupervised Deep Learning | cs.CV | We propose a novel monocular visual odometry (VO) system called UnDeepVO in
this paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera
and the depth of its view by using deep neural networks. There are two salient
features of the proposed UnDeepVO: one is the unsupervised deep learning
scheme, and th... | computer science |
29,541 | Learning quadrangulated patches for 3D shape parameterization and
completion | cs.CV | We propose a novel 3D shape parameterization by surface patches, that are
oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail
on local patches, we learn a patch dictionary that identifies principal surface
features of the shape. Unlike previous methods, we are able to encode surface
patches ... | computer science |
29,542 | Multi-camera Multi-Object Tracking | cs.CV | In this paper, we propose a pipeline for multi-target visual tracking under
multi-camera system. For multi-camera system tracking problem, efficient data
association across cameras, and at the same time, across frames becomes more
important than single-camera system tracking. However, most of the multi-camera
tracking ... | computer science |
29,543 | Semi-Automated Nasal PAP Mask Sizing using Facial Photographs | cs.CV | We present a semi-automated system for sizing nasal Positive Airway Pressure
(PAP) masks based upon a neural network model that was trained with facial
photographs of both PAP mask users and non-users. It demonstrated an accuracy
of 72% in correctly sizing a mask and 96% accuracy sizing to within 1 mask size
group. The... | computer science |
29,544 | Visual Question Generation as Dual Task of Visual Question Answering | cs.CV | Recently visual question answering (VQA) and visual question generation (VQG)
are two trending topics in the computer vision, which have been explored
separately. In this work, we propose an end-to-end unified framework, the
Invertible Question Answering Network (iQAN), to leverage the complementary
relations between q... | computer science |
29,545 | A First Derivative Potts Model for Segmentation and Denoising Using ILP | cs.CV | Unsupervised image segmentation and denoising are two fundamental tasks in
image processing. Usually, graph based models such as multicut are used for
segmentation and variational models are employed for denoising. Our approach
addresses both problems at the same time. We propose a novel ILP formulation of
the first de... | computer science |
29,546 | Human Pose Estimation using Global and Local Normalization | cs.CV | In this paper, we address the problem of estimating the positions of human
joints, i.e., articulated pose estimation. Recent state-of-the-art solutions
model two key issues, joint detection and spatial configuration refinement,
together using convolutional neural networks. Our work mainly focuses on
spatial configurati... | computer science |
29,547 | Playing for Benchmarks | cs.CV | We present a benchmark suite for visual perception. The benchmark is based on
more than 250K high-resolution video frames, all annotated with ground-truth
data for both low-level and high-level vision tasks, including optical flow,
semantic instance segmentation, object detection and tracking, object-level 3D
scene lay... | computer science |
29,548 | H-DenseUNet: Hybrid Densely Connected UNet for Liver and Liver Tumor
Segmentation from CT Volumes | cs.CV | Liver cancer is one of the leading causes of cancer death. To assist doctors
in hepatocellular carcinoma diagnosis and treatment planning, an accurate and
automatic liver and tumor segmentation method is highly demanded in the
clinical practice. Recently, fully convolutional neural networks (FCNs),
including 2D and 3D ... | computer science |
29,549 | Multi-label Pixelwise Classification for Reconstruction of Large-scale
Urban Areas | cs.CV | Object classification is one of the many holy grails in computer vision and
as such has resulted in a very large number of algorithms being proposed
already. Specifically in recent years there has been considerable progress in
this area primarily due to the increased efficiency and accessibility of deep
learning techni... | computer science |
29,550 | Urban Land Cover Classification with Missing Data Using Deep
Convolutional Neural Networks | cs.CV | Automatic urban land cover classification is a classical problem in remote
sensing and good urban land cover maps build the foundation for many tasks,
such as e.g. environmental monitoring. It is a particularly challenging
problem, as classes generally have high inter-class and low intra-class
variance. A common techni... | computer science |
29,551 | Learned Features are better for Ethnicity Classification | cs.CV | Ethnicity is a key demographic attribute of human beings and it plays a vital
role in automatic facial recognition and have extensive real world applications
such as Human Computer Interaction (HCI); demographic based classification;
biometric based recognition; security and defense to name a few. In this paper
we pres... | computer science |
29,552 | A Multimodal, Full-Surround Vehicular Testbed for Naturalistic Studies
and Benchmarking: Design, Calibration and Deployment | cs.CV | Recent progress in autonomous and semi-autonomous driving has been made
possible in part through an assortment of sensors that provide the intelligent
agent with an enhanced perception of its surroundings. It has been clear for
quite some while now that for intelligent vehicles to function effectively in
all situations... | computer science |
29,553 | Virtual Blood Vessels in Complex Background using Stereo X-ray Images | cs.CV | We propose a fully automatic system to reconstruct and visualize 3D blood
vessels in Augmented Reality (AR) system from stereo X-ray images with bones
and body fat. Currently, typical 3D imaging technologies are expensive and
carrying the risk of irradiation exposure. To reduce the potential harm, we
only need to take ... | computer science |
29,554 | Novel Evaluation Metrics for Seam Carving based Image Retargeting | cs.CV | Image retargeting effectively resizes images by preserving the
recognizability of important image regions. Most of retargeting methods rely on
good importance maps as a cue to retain or remove certain regions in the input
image. In addition, the traditional evaluation exhaustively depends on user
ratings. There is a le... | computer science |
29,555 | Smart Mirror: Intelligent Makeup Recommendation and Synthesis | cs.CV | The female facial image beautification usually requires professional editing
softwares, which are relatively difficult for common users. In this demo, we
introduce a practical system for automatic and personalized facial makeup
recommendation and synthesis. First, a model describing the relations among
facial features,... | computer science |
29,556 | Happy Travelers Take Big Pictures: A Psychological Study with Machine
Learning and Big Data | cs.CV | In psychology, theory-driven researches are usually conducted with extensive
laboratory experiments, yet rarely tested or disproved with big data. In this
paper, we make use of 418K travel photos with traveler ratings to test the
influential "broaden-and-build" theory, that suggests positive emotions broaden
one's visu... | computer science |
29,557 | Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic
Generative Adversarial Networks | cs.CV | Taking a photo outside, can we predict the immediate future, \textit{e.g.},
how would the cloud move in the sky? We address this problem by presenting a
generative adversarial network (GAN) based two-stage approach to generating
realistic time-lapse videos of high resolution. Given the first frame, our
model learns to ... | computer science |
29,558 | Demography-based Facial Retouching Detection using Subclass Supervised
Sparse Autoencoder | cs.CV | Digital retouching of face images is becoming more widespread due to the
introduction of software packages that automate the task. Several researchers
have introduced algorithms to detect whether a face image is original or
retouched. However, previous work on this topic has not considered whether or
how accuracy of re... | computer science |
29,559 | EraseReLU: A Simple Way to Ease the Training of Deep Convolution Neural
Networks | cs.CV | For most state-of-the-art architectures, Rectified Linear Unit (ReLU) becomes
a standard component accompanied with each layer. Although ReLU can ease the
network training to an extent, the character of blocking negative values may
suppress the propagation of useful information and leads to the difficulty of
optimizing... | computer science |
29,560 | SwGridNet: A Deep Convolutional Neural Network based on Grid Topology
for Image Classification | cs.CV | Deep convolutional neural networks (CNNs) achieve remarkable performance on
image classification tasks. Recent studies, however, have demonstrated that
generalization abilities are more important than the depth of neural networks
for improving performance on image classification tasks. Herein, a new neural
network call... | computer science |
29,561 | Can We Boost the Power of the Viola-Jones Face Detector Using
Pre-processing? An Empirical Study | cs.CV | The Viola-Jones face detection algorithm was (and still is) a quite popular
face detector. In spite of the numerous face detection techniques that have
been recently presented, there are many research works that are still based on
the Viola-Jones algorithm because of its simplicity. In this paper, we study
the influenc... | computer science |
29,562 | Tropical Land Use Land Cover Mapping in Pará (Brazil) using
Discriminative Markov Random Fields and Multi-temporal TerraSAR-X Data | cs.CV | Remote sensing satellite data offer the unique possibility to map land use
land cover transformations by providing spatially explicit information.
However, detection of short-term processes and land use patterns of high
spatial-temporal variability is a challenging task. We present a novel
framework using multi-tempora... | computer science |
29,563 | On Encoding Temporal Evolution for Real-time Action Prediction | cs.CV | Anticipating future actions is a key component of intelligence, specifically
when it applies to real-time systems, such as robots or autonomous cars. While
recent works have addressed prediction of raw RGB pixel values, we focus on
anticipating the motion evolution in future video frames. To this end, we
construct dyna... | computer science |
29,564 | Visual Reference Resolution using Attention Memory for Visual Dialog | cs.CV | Visual dialog is a task of answering a series of inter-dependent questions
given an input image, and often requires to resolve visual references among the
questions. This problem is different from visual question answering (VQA),
which relies on spatial attention (a.k.a. visual grounding) estimated from an
image and qu... | computer science |
29,565 | A semi-automated segmentation method for detection of pulmonary embolism
in True-FISP MRI sequences | cs.CV | Pulmonary embolism (PE) is a highly mortal disease, currently assessed by
pulmonary CT angiography. True-FISP MRI has emerged as an innocuous alternative
that does not hold many of the limitations of x-ray imaging. However, True-FISP
MRI is very sensitive to turbulent blood flow, generating artifacts that may
resemble ... | computer science |
29,566 | A Generic Regression Framework for Pose Recognition on Color and Depth
Images | cs.CV | Cascaded regression method is a fast and accurate method on finding 2D pose
of objects in RGB images. It is able to find the accurate pose of objects in an
image by a great number of corrections on the good initial guess of the pose of
objects. This paper explains the algorithm and shows the result of two
experiments c... | computer science |
29,567 | Compact Environment-Invariant Codes for Robust Visual Place Recognition | cs.CV | Robust visual place recognition (VPR) requires scene representations that are
invariant to various environmental challenges such as seasonal changes and
variations due to ambient lighting conditions during day and night. Moreover, a
practical VPR system necessitates compact representations of environmental
features. To... | computer science |
29,568 | Robust Facial Landmark Detection under Significant Head Poses and
Occlusion | cs.CV | There have been tremendous improvements for facial landmark detection on
general "in-the-wild" images. However, it is still challenging to detect the
facial landmarks on images with severe occlusion and images with large head
poses (e.g. profile face). In fact, the existing algorithms usually can only
handle one of the... | computer science |
29,569 | Constrained Deep Transfer Feature Learning and its Applications | cs.CV | Feature learning with deep models has achieved impressive results for both
data representation and classification for various vision tasks. Deep feature
learning, however, typically requires a large amount of training data, which
may not be feasible for some application domains. Transfer learning can be one
of the appr... | computer science |
29,570 | Constrained Joint Cascade Regression Framework for Simultaneous Facial
Action Unit Recognition and Facial Landmark Detection | cs.CV | Cascade regression framework has been shown to be effective for facial
landmark detection. It starts from an initial face shape and gradually predicts
the face shape update from the local appearance features to generate the facial
landmark locations in the next iteration until convergence. In this paper, we
improve upo... | computer science |
29,571 | Simultaneous Facial Landmark Detection, Pose and Deformation Estimation
under Facial Occlusion | cs.CV | Facial landmark detection, head pose estimation, and facial deformation
analysis are typical facial behavior analysis tasks in computer vision. The
existing methods usually perform each task independently and sequentially,
ignoring their interactions. To tackle this problem, we propose a unified
framework for simultane... | computer science |
29,572 | Domain Adaptation from Synthesis to Reality in Single-model Detector for
Video Smoke Detection | cs.CV | This paper proposes a method for video smoke detection using synthetic smoke
samples. The virtual data can automatically offer precise and rich annotated
samples. However, the learning of smoke representations will be hurt by the
appearance gap between real and synthetic smoke samples. The existed researches
mainly wor... | computer science |
29,573 | Comparison of Batch Normalization and Weight Normalization Algorithms
for the Large-scale Image Classification | cs.CV | Batch normalization (BN) has become a de facto standard for training deep
convolutional networks. However, BN accounts for a significant fraction of
training run-time and is difficult to accelerate, since it is a
memory-bandwidth bounded operation. Such a drawback of BN motivates us to
explore recently proposed weight ... | computer science |
29,574 | Tensor-Based Classifiers for Hyperspectral Data Analysis | cs.CV | In this work, we present tensor-based linear and nonlinear models for
hyperspectral data classification and analysis. By exploiting principles of
tensor algebra, we introduce new classification architectures, the weight
parameters of which satisfies the {\it rank}-1 canonical decomposition
property. Then, we introduce ... | computer science |
29,575 | Can Image Retrieval help Visual Saliency Detection? | cs.CV | We propose a novel image retrieval framework for visual saliency detection
using information about salient objects contained within bounding box
annotations for similar images. For each test image, we train a customized SVM
from similar example images to predict the saliency values of its object
proposals and generate ... | computer science |
29,576 | Performance Characterization of Image Feature Detectors in Relation to
the Scene Content Utilizing a Large Image Database | cs.CV | Selecting the most suitable local invariant feature detector for a particular
application has rendered the task of evaluating feature detectors a critical
issue in vision research. Although the literature offers a variety of
comparison works focusing on performance evaluation of image feature detectors
under several ty... | computer science |
29,577 | Survey of Recent Advances in Visual Question Answering | cs.CV | Visual Question Answering (VQA) presents a unique challenge as it requires
the ability to understand and encode the multi-modal inputs - in terms of image
processing and natural language processing. The algorithm further needs to
learn how to perform reasoning over this multi-modal representation so it can
answer the q... | computer science |
29,578 | 3D Camouflaging Object using RGB-D Sensors | cs.CV | This paper proposes a new optical camouflage system that uses RGB-D cameras,
for acquiring point cloud of background scene, and tracking observers eyes.
This system enables a user to conceal an object located behind a display that
surrounded by 3D objects. If we considered here the tracked point of observer s
eyes is a... | computer science |
29,579 | Fine-grained Discriminative Localization via Saliency-guided Faster
R-CNN | cs.CV | Discriminative localization is essential for fine-grained image
classification task, which devotes to recognizing hundreds of subcategories in
the same basic-level category. Reflecting on discriminative regions of objects,
key differences among different subcategories are subtle and local. Existing
methods generally ad... | computer science |
29,580 | Pose-driven Deep Convolutional Model for Person Re-identification | cs.CV | Feature extraction and matching are two crucial components in person
Re-Identification (ReID). The large pose deformations and the complex view
variations exhibited by the captured person images significantly increase the
difficulty of learning and matching of the features from person images. To
overcome these difficul... | computer science |
29,581 | Realizing Half-Diminished Reality from Video Stream of Manipulating
Objects | cs.CV | When we watch a video, in which human hands manipulate objects, these hands
may obscure some parts of those objects. We are willing to make clear how the
objects are manipulated by making the image of hands semi-transparent, and
showing the complete images of the hands and the object. By carefully choosing
a Half-Dimin... | computer science |
29,582 | An Evolutionary Computing Enriched RS Attack Resilient Medical Image
Steganography Model for Telemedicine Applications | cs.CV | The recent advancement in computing technologies and resulting vision based
applications have gives rise to a novel practice called telemedicine that
requires patient diagnosis images or allied information to recommend or even
perform diagnosis practices being located remotely. However, to ensure accurate
and optimal t... | computer science |
29,583 | Deep Sparse Subspace Clustering | cs.CV | In this paper, we present a deep extension of Sparse Subspace Clustering,
termed Deep Sparse Subspace Clustering (DSSC). Regularized by the unit sphere
distribution assumption for the learned deep features, DSSC can infer a new
data affinity matrix by simultaneously satisfying the sparsity principle of SSC
and the nonl... | computer science |
29,584 | Variational Reflectance Estimation from Multi-view Images | cs.CV | We tackle the problem of reflectance estimation from a set of multi-view
images, assuming known geometry. The approach we put forward turns the input
images into reflectance maps, through a robust variational method. The
variational model comprises an image-driven fidelity term and a term which
enforces consistency of ... | computer science |
29,585 | Multi-view Registration Based on Weighted Low Rank and Sparse Matrix
Decomposition of Motions | cs.CV | Recently, the low rank and sparse (LRS) matrix decomposition has been
introduced as an effective mean to solve the multi-view registration. However,
this method presents two notable disadvantages: the registration result is
quite sensitive to the sparsity of the LRS matrix; besides, the decomposition
process treats eac... | computer science |
29,586 | Morphable Face Models - An Open Framework | cs.CV | In this paper, we present a novel open-source pipeline for face registration
based on Gaussian processes as well as an application to face image analysis.
Non-rigid registration of faces is significant for many applications in
computer vision, such as the construction of 3D Morphable face models (3DMMs).
Gaussian Proce... | computer science |
29,587 | Summarization of User-Generated Sports Video by Using Deep Action
Recognition Features | cs.CV | Automatically generating a summary of sports video poses the challenge of
detecting interesting moments, or highlights, of a game. Traditional sports
video summarization methods leverage editing conventions of broadcast sports
video that facilitate the extraction of high-level semantics. However,
user-generated videos ... | computer science |
29,588 | Multi-view pose estimation with mixtures-of-parts and adaptive viewpoint
selection | cs.CV | We propose a new method for human pose estimation which leverages information
from multiple views to impose a strong prior on articulated pose. The novelty
of the method concerns the types of coherence modelled. Consistency is
maximised over the different views through different terms modelling classical
geometric info... | computer science |
29,589 | Attribute Recognition by Joint Recurrent Learning of Context and
Correlation | cs.CV | Recognising semantic pedestrian attributes in surveillance images is a
challenging task for computer vision, particularly when the imaging quality is
poor with complex background clutter and uncontrolled viewing conditions, and
the number of labelled training data is small. In this work, we formulate a
Joint Recurrent ... | computer science |
29,590 | Dense scale selection over space, time and space-time | cs.CV | Scale selection methods based on local extrema over scale of scale-normalized
derivatives have been primarily developed to be applied sparsely --- at image
points where the magnitude of a scale-normalized differential expression
additionally assumes local extrema over the domain where the data are defined.
This paper p... | computer science |
29,591 | Fast Vehicle Detection in Aerial Imagery | cs.CV | In recent years, several real-time or near real-time object detectors have
been developed. However these object detectors are typically designed for
first-person view images where the subject is large in the image and do not
directly apply well to detecting vehicles in aerial imagery. Though some
detectors have been de... | computer science |
29,592 | Multimodal Image Super-resolution via Joint Sparse Representations
induced by Coupled Dictionaries | cs.CV | Real-world data processing problems often involve various image modalities
associated with a certain scene, including RGB images, infrared images or
multi-spectral images. The fact that different image modalities often share
certain attributes, such as certain edges, textures and other structure
primitives, represents ... | computer science |
29,593 | Camera-Aware Multi-Resolution Analysis (CAMRA) for Raw Sensor Data
Compression | cs.CV | We propose a novel lossless and lossy compression scheme for color filter
array~(CFA) sampled images based on the wavelet transform of them. Our analysis
suggests that the wavelet coefficients of HL and LH subbands are highly
correlated. Hence, we decorrelate Mallat wavelet packet decomposition to
further sparsify the ... | computer science |
29,594 | Image similarity using Deep CNN and Curriculum Learning | cs.CV | Image similarity involves fetching similar looking images given a reference
image. Our solution called SimNet, is a deep siamese network which is trained
on pairs of positive and negative images using a novel online pair mining
strategy inspired by Curriculum learning. We also created a multi-scale CNN,
where the final... | computer science |
29,595 | Towards End-to-End Car License Plates Detection and Recognition with
Deep Neural Networks | cs.CV | In this work, we tackle the problem of car license plate detection and
recognition in natural scene images. We propose a unified deep neural network
which can localize license plates and recognize the letters simultaneously in a
single forward pass. The whole network can be trained end-to-end. In contrast
to existing a... | computer science |
29,596 | Learning to Inpaint for Image Compression | cs.CV | We study the design of deep architectures for lossy image compression. We
present two architectural recipes in the context of multi-stage progressive
encoders and empirically demonstrate their importance on compression
performance. Specifically, we show that: (a) predicting the original image data
from residuals in a m... | computer science |
29,597 | UBSegNet: Unified Biometric Region of Interest Segmentation Network | cs.CV | Digital human identity management, can now be seen as a social necessity, as
it is essentially required in almost every public sector such as, financial
inclusions, security, banking, social networking e.t.c. Hence, in today's
rampantly emerging world with so many adversarial entities, relying on a single
biometric tra... | computer science |
29,598 | Multi-layer Visualization for Medical Mixed Reality | cs.CV | Medical Mixed Reality helps surgeons to contextualize intraoperative data
with video of the surgical scene. Nonetheless, the surgical scene and
anatomical target are often occluded by surgical instruments and surgeon hands.
In this paper and to our knowledge, we propose a multi-layer visualization in
Medical Mixed Real... | computer science |
29,599 | Automated sub-cortical brain structure segmentation combining spatial
and deep convolutional features | cs.CV | Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI)
has attracted the interest of the research community for a long time because
morphological changes in these structures are related to different
neurodegenerative disorders. However, manual segmentation of these structures
can be tedious and pr... | computer science |
29,600 | Joint Detection and Recounting of Abnormal Events by Learning Deep
Generic Knowledge | cs.CV | This paper addresses the problem of joint detection and recounting of
abnormal events in videos. Recounting of abnormal events, i.e., explaining why
they are judged to be abnormal, is an unexplored but critical task in video
surveillance, because it helps human observers quickly judge if they are false
alarms or not. T... | computer science |
29,601 | Understanding Infographics through Textual and Visual Tag Prediction | cs.CV | We introduce the problem of visual hashtag discovery for infographics:
extracting visual elements from an infographic that are diagnostic of its
topic. Given an infographic as input, our computational approach automatically
outputs textual and visual elements predicted to be representative of the
infographic content. C... | computer science |
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