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30,502 | Learning Surrogate Models of Document Image Quality Metrics for
Automated Document Image Processing | cs.CV | Computation of document image quality metrics often depends upon the
availability of a ground truth image corresponding to the document. This limits
the applicability of quality metrics in applications such as hyperparameter
optimization of image processing algorithms that operate on-the-fly on unseen
documents. This w... | computer science |
30,503 | Deep convolutional neural networks for brain image analysis on magnetic
resonance imaging: a review | cs.CV | In recent years, deep convolutional neural networks (CNNs) have shown
record-shattering performance in a variety of computer vision problems, such as
visual object recognition, detection and segmentation. These methods have also
been utilized in medical image analysis domain for lesion segmentation,
anatomical segmenta... | computer science |
30,504 | Error Correction for Dense Semantic Image Labeling | cs.CV | Pixelwise semantic image labeling is an important, yet challenging, task with
many applications. Typical approaches to tackle this problem involve either the
training of deep networks on vast amounts of images to directly infer the
labels or the use of probabilistic graphical models to jointly model the
dependencies of... | computer science |
30,505 | Variational models for joint subsampling and reconstruction of
turbulence-degraded images | cs.CV | Turbulence-degraded image frames are distorted by both turbulent deformations
and space-time-varying blurs. To suppress these effects, we propose a
multi-frame reconstruction scheme to recover a latent image from the observed
image sequence. Recent approaches are commonly based on registering each frame
to a reference ... | computer science |
30,506 | Unsupervised Feature Learning for Audio Analysis | cs.CV | Identifying acoustic events from a continuously streaming audio source is of
interest for many applications including environmental monitoring for basic
research. In this scenario neither different event classes are known nor what
distinguishes one class from another. Therefore, an unsupervised feature
learning method ... | computer science |
30,507 | Using a single RGB frame for real time 3D hand pose estimation in the
wild | cs.CV | We present a method for the real-time estimation of the full 3D pose of one
or more human hands using a single commodity RGB camera. Recent work in the
area has displayed impressive progress using RGBD input. However, since the
introduction of RGBD sensors, there has been little progress for the case of
monocular color... | computer science |
30,508 | Feature Mapping for Learning Fast and Accurate 3D Pose Inference from
Synthetic Images | cs.CV | We propose a simple and efficient method for exploiting synthetic images when
training a Deep Network to predict a 3D pose from an image. The ability of
using synthetic images for training a Deep Network is extremely valuable as it
is easy to create a virtually infinite training set made of such images, while
capturing... | computer science |
30,509 | 3D Hand Pose Estimation: From Current Achievements to Future Goals | cs.CV | In this paper, we strive to answer two questions: What is the current state
of 3D hand pose estimation? And, what are the next challenges that need to be
tackled? Following the successful Hands In the Million Challenge (HIM2017), we
investigate 11 state-of-the-art methods on three tasks: single frame 3D pose
estimation... | computer science |
30,510 | A GRU-based Encoder-Decoder Approach with Attention for Online
Handwritten Mathematical Expression Recognition | cs.CV | In this study, we present a novel end-to-end approach based on the
encoder-decoder framework with the attention mechanism for online handwritten
mathematical expression recognition (OHMER). First, the input two-dimensional
ink trajectory information of handwritten expression is encoded via the gated
recurrent unit base... | computer science |
30,511 | Learning Compressible 360° Video Isomers | cs.CV | Standard video encoders developed for conventional narrow field-of-view video
are widely applied to 360{\deg} video as well, with reasonable results.
However, while this approach commits arbitrarily to a projection of the
spherical frames, we observe that some orientations of a 360{\deg} video, once
projected, are more... | computer science |
30,512 | Im2Flow: Motion Hallucination from Static Images for Action Recognition | cs.CV | Existing methods to recognize actions in static images take the images at
their face value, learning the appearances---objects, scenes, and body
poses---that distinguish each action class. However, such models are deprived
of the rich dynamic structure and motions that also define human activity. We
propose an approach... | computer science |
30,513 | 200x Low-dose PET Reconstruction using Deep Learning | cs.CV | Positron emission tomography (PET) is widely used in various clinical
applications, including cancer diagnosis, heart disease and neuro disorders.
The use of radioactive tracer in PET imaging raises concerns due to the risk of
radiation exposure. To minimize this potential risk in PET imaging, efforts
have been made to... | computer science |
30,514 | A vision based system for underwater docking | cs.CV | Autonomous underwater vehicles (AUVs) have been deployed for underwater
exploration. However, its potential is confined by its limited on-board battery
energy and data storage capacity. This problem has been addressed using docking
systems by underwater recharging and data transfer for AUVs. In this work, we
propose a ... | computer science |
30,515 | Direction-aware Spatial Context Features for Shadow Detection | cs.CV | Shadow detection is a fundamental and challenging task, since it requires an
understanding of global image semantics and there are various backgrounds
around shadows. This paper presents a novel network for shadow detection by
analyzing image context in a direction-aware manner. To achieve this, we first
formulate the ... | computer science |
30,516 | Review. Machine learning techniques for traffic sign detection | cs.CV | An automatic road sign detection system localizes road signs from within
images captured by an on-board camera of a vehicle, and support the driver to
properly ride the vehicle. Most existing algorithms include a preprocessing
step, feature extraction and detection step. This paper arranges the methods
applied to road ... | computer science |
30,517 | Conditional Generative Adversarial Networks for Emoji Synthesis with
Word Embedding Manipulation | cs.CV | Emojis have become a very popular part of daily digital communication. Their
appeal comes largely in part due to their ability to capture and elicit
emotions in a more subtle and nuanced way than just plain text is able to. In
line with recent advances in the field of deep learning, there are far reaching
implications ... | computer science |
30,518 | 3D Object Classification via Spherical Projections | cs.CV | In this paper, we introduce a new method for classifying 3D objects. Our main
idea is to project a 3D object onto a spherical domain centered around its
barycenter and develop neural network to classify the spherical projection. We
introduce two complementary projections. The first captures depth variations of
a 3D obj... | computer science |
30,519 | Data Distillation: Towards Omni-Supervised Learning | cs.CV | We investigate omni-supervised learning, a special regime of semi-supervised
learning in which the learner exploits all available labeled data plus
internet-scale sources of unlabeled data. Omni-supervised learning is
lower-bounded by performance on existing labeled datasets, offering the
potential to surpass state-of-... | computer science |
30,520 | Learning a Complete Image Indexing Pipeline | cs.CV | To work at scale, a complete image indexing system comprises two components:
An inverted file index to restrict the actual search to only a subset that
should contain most of the items relevant to the query; An approximate distance
computation mechanism to rapidly scan these lists. While supervised deep
learning has re... | computer science |
30,521 | Fingerprint Spoof Buster | cs.CV | The primary purpose of a fingerprint recognition system is to ensure a
reliable and accurate user authentication, but the security of the recognition
system itself can be jeopardized by spoof attacks. This study addresses the
problem of developing accurate, generalizable, and efficient algorithms for
detecting fingerpr... | computer science |
30,522 | Camera Calibration for Daylight Specular-Point Locus | cs.CV | In this paper we present a new camera calibration method aimed at finding a
straight-line locus, in a special colour feature space, that is traversed by
daylights and as well also approximately followed by specular points. The aim
of the calibration is to enable recovering the colour of the illuminant in a
scene, using... | computer science |
30,523 | Im2Pano3D: Extrapolating 360 Structure and Semantics Beyond the Field of
View | cs.CV | We present Im2Pano3D, a convolutional neural network that generates a dense
prediction of 3D structure and a probability distribution of semantic labels
for a full 360 panoramic view of an indoor scene when given only a partial
observation (<= 50%) in the form of an RGB-D image. To make this possible,
Im2Pano3D leverag... | computer science |
30,524 | Fusing Multiple Multiband Images | cs.CV | We consider the problem of fusing an arbitrary number of multiband, i.e.,
panchromatic, multispectral, or hyperspectral, images belonging to the same
scene. We use the well-known forward observation and linear mixture models with
Gaussian perturbations to formulate the maximum-likelihood estimator of the
endmember abun... | computer science |
30,525 | Transfer Adversarial Hashing for Hamming Space Retrieval | cs.CV | Hashing is widely applied to large-scale image retrieval due to the storage
and retrieval efficiency. Existing work on deep hashing assumes that the
database in the target domain is identically distributed with the training set
in the source domain. This paper relaxes this assumption to a transfer
retrieval setting, wh... | computer science |
30,526 | The Effectiveness of Data Augmentation in Image Classification using
Deep Learning | cs.CV | In this paper, we explore and compare multiple solutions to the problem of
data augmentation in image classification. Previous work has demonstrated the
effectiveness of data augmentation through simple techniques, such as cropping,
rotating, and flipping input images. We artificially constrain our access to
data to a ... | computer science |
30,527 | Learning Disentangling and Fusing Networks for Face Completion Under
Structured Occlusions | cs.CV | Face completion aims to generate semantically new pixels for missing facial
components. It is a challenging generative task due to large variations of face
appearance. This paper studies generative face completion under structured
occlusions. We treat the face completion and corruption as disentangling and
fusing proce... | computer science |
30,528 | UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face
Recognition | cs.CV | Recently proposed robust 3D face alignment methods establish either dense or
sparse correspondence between a 3D face model and a 2D facial image. The use of
these methods presents new challenges as well as opportunities for facial
texture analysis. In particular, by sampling the image using the fitted model,
a facial U... | computer science |
30,529 | The Enhanced Hybrid MobileNet | cs.CV | Although complicated and deep neural network models can achieve high accuracy
of image recognition, they require huge amount of computations and parameters
and are not suitable for mobile and embedded devices. As a result, MobileNet
was proposed, which can reduce the amount of parameters and computational cost
dramatic... | computer science |
30,530 | Regularization and Optimization strategies in Deep Convolutional Neural
Network | cs.CV | Convolution Neural Networks, known as ConvNets exceptionally perform well in
many complex machine learning tasks. The architecture of ConvNets demands the
huge and rich amount of data and involves with a vast number of parameters that
leads the learning takes to be computationally expensive, slow convergence
towards th... | computer science |
30,531 | GMM-Based Synthetic Samples for Classification of Hyperspectral Images
With Limited Training Data | cs.CV | The amount of training data that is required to train a classifier scales
with the dimensionality of the feature data. In hyperspectral remote sensing,
feature data can potentially become very high dimensional. However, the amount
of training data is oftentimes limited. Thus, one of the core challenges in
hyperspectral... | computer science |
30,532 | Symbol detection in online handwritten graphics using Faster R-CNN | cs.CV | Symbol detection techniques in online handwritten graphics (e.g. diagrams and
mathematical expressions) consist of methods specifically designed for a single
graphic type. In this work, we evaluate the Faster R-CNN object detection
algorithm as a general method for detection of symbols in handwritten graphics.
We evalu... | computer science |
30,533 | MaskLab: Instance Segmentation by Refining Object Detection with
Semantic and Direction Features | cs.CV | In this work, we tackle the problem of instance segmentation, the task of
simultaneously solving object detection and semantic segmentation. Towards this
goal, we present a model, called MaskLab, which produces three outputs: box
detection, semantic segmentation, and direction prediction. Building on top of
the Faster-... | computer science |
30,534 | Self-Supervised Depth Learning for Urban Scene Understanding | cs.CV | As an agent moves through the world, the apparent motion of scene elements is
(usually) inversely proportional to their depth. It is natural for a learning
agent to associate image patterns with the magnitude of their displacement over
time: as the agent moves, far away mountains don't move much; nearby trees move
a lo... | computer science |
30,535 | Rethinking Spatiotemporal Feature Learning For Video Understanding | cs.CV | In this paper we study 3D convolutional networks for video understanding
tasks. Our starting point is the state-of-the-art I3D model, which "inflates"
all the 2D filters of the Inception architecture to 3D. We first consider
"deflating" the I3D model at various levels to understand the role of 3D
convolutions. Interest... | computer science |
30,536 | Object Classification using Ensemble of Local and Deep Features | cs.CV | In this paper we propose an ensemble of local and deep features for object
classification. We also compare and contrast effectiveness of feature
representation capability of various layers of convolutional neural network. We
demonstrate with extensive experiments for object classification that the
representation capabi... | computer science |
30,537 | Enhanced Characterness for Text Detection in the Wild | cs.CV | Text spotting is an interesting research problem as text may appear at any
random place and may occur in various forms. Moreover, ability to detect text
opens the horizons for improving many advanced computer vision problems. In
this paper, we propose a novel language agnostic text detection method
utilizing edge enhan... | computer science |
30,538 | Real-time Egocentric Gesture Recognition on Mobile Head Mounted Displays | cs.CV | Mobile virtual reality (VR) head mounted displays (HMD) have become popular
among consumers in recent years. In this work, we demonstrate real-time
egocentric hand gesture detection and localization on mobile HMDs. Our main
contributions are: 1) A novel mixed-reality data collection tool to automatic
annotate bounding ... | computer science |
30,539 | Unsupervised Histopathology Image Synthesis | cs.CV | Hematoxylin and Eosin stained histopathology image analysis is essential for
the diagnosis and study of complicated diseases such as cancer. Existing
state-of-the-art approaches demand extensive amount of supervised training data
from trained pathologists. In this work we synthesize in an unsupervised
manner, large his... | computer science |
30,540 | Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks | cs.CV | Skeletal bone age assessment is a common clinical practice to diagnose
endocrine and metabolic disorders in child development. In this paper, we
describe a fully automated deep learning approach to the problem of bone age
assessment using data from Pediatric Bone Age Challenge organized by RSNA 2017.
The dataset for th... | computer science |
30,541 | MentorNet: Regularizing Very Deep Neural Networks on Corrupted Labels | cs.CV | Recent studies have discovered that deep networks are capable of memorizing
the entire data even when the labels are completely random. Since deep models
are trained on big data where labels are often noisy, the ability to overfit
noise can lead to poor performance. To overcome the overfitting on corrupted
training dat... | computer science |
30,542 | Weakly Supervised Action Localization by Sparse Temporal Pooling Network | cs.CV | We propose a weakly supervised temporal action localization algorithm on
untrimmed videos using convolutional neural networks. Our algorithm predicts
temporal intervals of human actions given video-level class labels with no
requirement of temporal localization information of actions. This objective is
achieved by prop... | computer science |
30,543 | Extreme 3D Face Reconstruction: Looking Past Occlusions | cs.CV | Existing single view, 3D face reconstruction methods can produce beautifully
detailed 3D results, but typically only for near frontal, unobstructed
viewpoints. We describe a system designed to provide detailed 3D
reconstructions of faces viewed under extreme conditions, out of plane
rotations, and occlusions. Motivated... | computer science |
30,544 | Detection and Attention: Diagnosing Pulmonary Lung Cancer from CT by
Imitating Physicians | cs.CV | This paper proposes a novel and efficient method to build a Computer-Aided
Diagnoses (CAD) system for lung nodule detection based on Computed Tomography
(CT). This task was treated as an Object Detection on Video (VID) problem by
imitating how a radiologist reads CT scans. A lung nodule detector was trained
to automati... | computer science |
30,545 | Multi-appearance Segmentation and Extended 0-1 Program for Dense Small
Object Tracking | cs.CV | Aiming to address the fast multi-object tracking for dense small object in
the cluster background, we review track orientated multi-hypothesis
tracking(TOMHT) with consideration of batch optimization. Employing
autocorrelation based motion score test and staged hypotheses merging approach,
we build our homologous hypot... | computer science |
30,546 | Semi-Automatic Algorithm for Breast MRI Lesion Segmentation Using
Marker-Controlled Watershed Transformation | cs.CV | Magnetic resonance imaging (MRI) is an effective imaging modality for
identifying and localizing breast lesions in women. Accurate and precise lesion
segmentation using a computer-aided-diagnosis (CAD) system, is a crucial step
in evaluating tumor volume and in the quantification of tumor characteristics.
However, this... | computer science |
30,547 | Robust Estimation of Similarity Transformation for Visual Object
Tracking with Correlation Filters | cs.CV | Most of existing correlation filter-based tracking approaches only estimate
simple axis-aligned bounding boxes, and very few of them is capable of
recovering the underlying similarity transformation. To a large extent, such
limitation restricts the applications of such trackers for a wide range of
scenarios. In this pa... | computer science |
30,548 | Image Super-resolution via Feature-augmented Random Forest | cs.CV | Recent random-forest (RF)-based image super-resolution approaches inherit
some properties from dictionary-learning-based algorithms, but the
effectiveness of the properties in RF is overlooked in the literature. In this
paper, we present a novel feature-augmented random forest (FARF) for image
super-resolution, where t... | computer science |
30,549 | A Performance Evaluation of Local Features for Image Based 3D
Reconstruction | cs.CV | This paper performs a comprehensive and comparative evaluation of the state
of the art local features for the task of image based 3D reconstruction. The
evaluated local features cover the recently developed ones by using powerful
machine learning techniques and the elaborately designed handcrafted features.
To obtain a... | computer science |
30,550 | Face-from-Depth for Head Pose Estimation on Depth Images | cs.CV | Depth cameras allow to setup reliable solutions for people monitoring and
behavior understanding, specially when unstable or poor illumination conditions
make unusable common RGB sensors. Therefore, we propose a complete framework
for the estimation of the head and shoulder pose based on depth images only. A
head detec... | computer science |
30,551 | Deep CNN ensembles and suggestive annotations for infant brain MRI
segmentation | cs.CV | Precise 3D segmentation of infant brain tissues is an essential step towards
comprehensive volumetric studies and quantitative analysis of early brain
developement. However, computing such segmentations is very challenging,
especially for 6-month infant brain, due to the poor image quality, among other
difficulties inh... | computer science |
30,552 | SEE: Towards Semi-Supervised End-to-End Scene Text Recognition | cs.CV | Detecting and recognizing text in natural scene images is a challenging, yet
not completely solved task. In recent years several new systems that try to
solve at least one of the two sub-tasks (text detection and text recognition)
have been proposed. In this paper we present SEE, a step towards
semi-supervised neural n... | computer science |
30,553 | RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality
Assessment | cs.CV | Inspired by the free-energy brain theory, which implies that human visual
system (HVS) tends to reduce uncertainty and restore perceptual details upon
seeing a distorted image, we propose restorative adversarial net (RAN), a
GAN-based model for no-reference image quality assessment (NR-IQA). RAN, which
mimics the proce... | computer science |
30,554 | Visual Based Navigation of Mobile Robots | cs.CV | We have developed an algorithm to generate a complete map of the traversable
region for a personal assistant robot using monocular vision only. Using
multiple taken by a simple webcam, obstacle detection and avoidance algorithms
have been developed. Simple Linear Iterative Clustering (SLIC) has been used
for segmentati... | computer science |
30,555 | Transfer Learning for OCRopus Model Training on Early Printed Books | cs.CV | A method is presented that significantly reduces the character error rates
for OCR text obtained from OCRopus models trained on early printed books when
only small amounts of diplomatic transcriptions are available. This is achieved
by building from already existing models during training instead of starting
from scrat... | computer science |
30,556 | Fast Hough Transform and approximation properties of dyadic patterns | cs.CV | Hough transform is a popular low-level computer vision algorithm. Its
computationally effective modification, Fast Hough transform (FHT), makes use
of special subsets of image matrix to approximate geometric lines on it.
Because of their special structure, these subset are called dyadic patterns.
In this paper variou... | computer science |
30,557 | Automated Image Analysis Framework for the High-Throughput Determination
of Grapevine Berry Sizes Using Conditional Random Fields | cs.CV | The berry size is one of the most important fruit traits in grapevine
breeding. Non-invasive, image-based phenotyping promises a fast and precise
method for the monitoring of the grapevine berry size. In the present study an
automated image analyzing framework was developed in order to estimate the size
of grapevine be... | computer science |
30,558 | Unsupervised Domain Adaptation for 3D Keypoint Prediction from a Single
Depth Scan | cs.CV | In this paper, we introduce a novel unsupervised domain adaptation technique
for the task of 3D keypoint prediction from a single depth scan/image. Our key
idea is to utilize the fact that predictions from different views of the same
or similar objects should be consistent with each other. Such view consistency
provide... | computer science |
30,559 | Semantic Visual Localization | cs.CV | Robust visual localization under a wide range of viewing conditions is a
fundamental problem in computer vision. Handling the difficult cases of this
problem is not only very challenging but also of high practical relevance,
e.g., in the context of life-long localization for augmented reality or
autonomous robots. In t... | computer science |
30,560 | Multi-Attribute Robust Component Analysis for Facial UV Maps | cs.CV | Recently, due to the collection of large scale 3D face models, as well as the
advent of deep learning, a significant progress has been made in the field of
3D face alignment "in-the-wild". That is, many methods have been proposed that
establish sparse or dense 3D correspondences between a 2D facial image and a 3D
face ... | computer science |
30,561 | Mapping the world population one building at a time | cs.CV | High resolution datasets of population density which accurately map
sparsely-distributed human populations do not exist at a global scale.
Typically, population data is obtained using censuses and statistical modeling.
More recently, methods using remotely-sensed data have emerged, capable of
effectively identifying ur... | computer science |
30,562 | Impression Network for Video Object Detection | cs.CV | Video object detection is more challenging compared to image object
detection. Previous works proved that applying object detector frame by frame
is not only slow but also inaccurate. Visual clues get weakened by defocus and
motion blur, causing failure on corresponding frames. Multi-frame feature
fusion methods proved... | computer science |
30,563 | SRPGAN: Perceptual Generative Adversarial Network for Single Image Super
Resolution | cs.CV | Single image super resolution (SISR) is to reconstruct a high resolution
image from a single low resolution image. The SISR task has been a very
attractive research topic over the last two decades. In recent years,
convolutional neural network (CNN) based models have achieved great performance
on SISR task. Despite the... | computer science |
30,564 | Learning a Virtual Codec Based on Deep Convolutional Neural Network to
Compress Image | cs.CV | Although deep convolutional neural network has been proved to efficiently
eliminate coding artifacts caused by the coarse quantization of traditional
codec, it's difficult to train any neural network in front of the encoder for
gradient's back-propagation. In this paper, we propose an end-to-end image
compression frame... | computer science |
30,565 | An ILP Solver for Multi-label MRFs with Connectivity Constraints | cs.CV | Integer Linear Programming (ILP) formulations of Markov random fields (MRFs)
models with global connectivity priors were investigated previously in computer
vision, e.g., \cite{globalinter,globalconn}. In these works, only Linear
Programing (LP) relaxations \cite{globalinter,globalconn} or simplified
versions \cite{gra... | computer science |
30,566 | Spatial As Deep: Spatial CNN for Traffic Scene Understanding | cs.CV | Convolutional neural networks (CNNs) are usually built by stacking
convolutional operations layer-by-layer. Although CNN has shown strong
capability to extract semantics from raw pixels, its capacity to capture
spatial relationships of pixels across rows and columns of an image is not
fully explored. These relationship... | computer science |
30,567 | Railway Track Specific Traffic Signal Selection Using Deep Learning | cs.CV | With the railway transportation Industry moving actively towards automation,
accurate location and inventory of wayside track assets like traffic signals,
crossings, switches, mileposts, etc. is of extreme importance. With the new
Positive Train Control (PTC) regulation coming into effect, many railway safety
rules wil... | computer science |
30,568 | Learning a Single Convolutional Super-Resolution Network for Multiple
Degradations | cs.CV | Recent years have witnessed the unprecedented success of deep convolutional
neural networks (CNNs) in single image super-resolution (SISR). However,
existing CNN-based SISR methods mostly assume that a low-resolution (LR) image
is bicubicly downsampled from a high-resolution (HR) image, thus inevitably
giving rise to p... | computer science |
30,569 | clcNet: Improving the Efficiency of Convolutional Neural Network using
Channel Local Convolutions | cs.CV | Depthwise convolution and grouped convolution has been successfully applied
to improve the efficiency of convolutional neural network (CNN). We suggest
that these models can be considered as special cases of a generalized
convolution operation, named channel local convolution(CLC), where an output
channel is computed u... | computer science |
30,570 | LSTM Pose Machines | cs.CV | We observed that recent state-of-the-art results on single image human pose
estimation were achieved by multi-stage Convolution Neural Networks (CNN).
Notwithstanding the superior performance on static images, the application of
these models on videos is not only computationally intensive, it also suffers
from performa... | computer science |
30,571 | Object Detection with an Aligned Spatial-Temporal Memory | cs.CV | We introduce Spatial-Temporal Memory Networks (STMN) for object detection in
videos. At its core, we propose a novel Spatial-Temporal Memory module (STMM)
as the recurrent computation unit to model long-term temporal appearance and
motion dynamics. The STMM's design enables the full integration of pretrained
backbone C... | computer science |
30,572 | Space-Filling Curve Indices as Acceleration Structure for Exemplar-Based
Inpainting | cs.CV | Exemplar-based inpainting is the process of reconstructing missing parts of
an image by searching the remaining data for patches that fit seamlessly. The
image is completed to a plausible-looking solution by repeatedly inserting the
patch that is the best match according to some cost function. We present an
acceleratio... | computer science |
30,573 | Automatic Classification of Functional Gait Disorders | cs.CV | This article proposes a comprehensive investigation of the automatic
classification of functional gait disorders based solely on ground reaction
force (GRF) measurements. The aim of the study is twofold: (1) to investigate
the suitability of stateof-the-art GRF parameterization techniques
(representations) for the disc... | computer science |
30,574 | Automatic segmentation method of pelvic floor levator hiatus in
ultrasound using a self-normalising neural network | cs.CV | Segmentation of the levator hiatus in ultrasound allows to extract biometrics
which are of importance for pelvic floor disorder assessment. In this work, we
present a fully automatic method using a convolutional neural network (CNN) to
outline the levator hiatus in a 2D image extracted from a 3D ultrasound volume.
In p... | computer science |
30,575 | Super-Resolution with Deep Adaptive Image Resampling | cs.CV | Deep learning based methods have recently pushed the state-of-the-art on the
problem of Single Image Super-Resolution (SISR). In this work, we revisit the
more traditional interpolation-based methods, that were popular before, now
with the help of deep learning. In particular, we propose to use a
Convolutional Neural N... | computer science |
30,576 | Multi-modal Face Pose Estimation with Multi-task Manifold Deep Learning | cs.CV | Human face pose estimation aims at estimating the gazing direction or head
postures with 2D images. It gives some very important information such as
communicative gestures, saliency detection and so on, which attracts plenty of
attention recently. However, it is challenging because of complex background,
various orient... | computer science |
30,577 | Guiding human gaze with convolutional neural networks | cs.CV | The eye fixation patterns of human observers are a fundamental indicator of
the aspects of an image to which humans attend. Thus, manipulating fixation
patterns to guide human attention is an exciting challenge in digital image
processing. Here, we present a new model for manipulating images to change the
distribution ... | computer science |
30,578 | Multi-point Vibration Measurement for Mode Identification of Bridge
Structures using Video-based Motion Magnification | cs.CV | Image-based vibration mode identification gained increased attentions in
civil and construction communities. A recent video-based motion magnification
method was developed to measure and visualize small structure motions. This new
approach presents a potential for low-cost vibration measurement and mode shape
identific... | computer science |
30,579 | End-to-end Recovery of Human Shape and Pose | cs.CV | We describe Human Mesh Recovery (HMR), an end-to-end framework for
reconstructing a full 3D mesh of a human body from a single RGB image. In
contrast to most current methods that compute 2D or 3D joint locations, we
produce a richer and more useful mesh representation that is parameterized by
shape and 3D joint angles.... | computer science |
30,580 | DecideNet: Counting Varying Density Crowds Through Attention Guided
Detection and Density Estimation | cs.CV | In real-world crowd counting applications, the crowd densities vary greatly
in spatial and temporal domains. A detection based counting method will
estimate crowds accurately in low density scenes, while its reliability in
congested areas is downgraded. A regression based approach, on the other hand,
captures the gener... | computer science |
30,581 | PixelBNN: Augmenting the PixelCNN with batch normalization and the
presentation of a fast architecture for retinal vessel segmentation | cs.CV | Analysis of retinal fundus images is essential for eye-care physicians in the
diagnosis, care and treatment of patients. Accurate fundus and/or retinal
vessel maps give rise to longitudinal studies able to utilize multimedia image
registration and disease/condition status measurements, as well as applications
in surger... | computer science |
30,582 | Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds | cs.CV | Unlike on images, semantic learning on 3D point clouds using a deep network
is challenging due to the naturally unordered data structure. Among existing
works, PointNet has achieved promising results by directly learning on point
sets. However, it does not take full advantage of a point's local neighborhood
that contai... | computer science |
30,583 | MovieGraphs: Towards Understanding Human-Centric Situations from Videos | cs.CV | There is growing interest in artificial intelligence to build socially
intelligent robots. This requires machines to have the ability to "read"
people's emotions, motivations, and other factors that affect behavior. Towards
this goal, we introduce a novel dataset called MovieGraphs which provides
detailed, graph-based ... | computer science |
30,584 | Hierarchical Cross Network for Person Re-identification | cs.CV | Person re-identification (person re-ID) aims at matching target person(s)
grabbed from different and non-overlapping camera views. It plays an important
role for public safety and has application in various tasks such as, human
retrieval, human tracking, and activity analysis. In this paper, we propose a
new network ar... | computer science |
30,585 | Single Image Deraining using Scale-Aware Multi-Stage Recurrent Network | cs.CV | Given a single input rainy image, our goal is to visually remove rain streaks
and the veiling effect caused by scattering and transmission of rain streaks
and rain droplets. We are particularly concerned with heavy rain, where rain
streaks of various sizes and directions can overlap each other and the veiling
effect re... | computer science |
30,586 | Comparison of fingerprint authentication algorithms for small imaging
sensors | cs.CV | The demand for biometric systems has been increasing with the growth of the
smartphone market. Biometric devices allow the user to authenticate easily
while securing its private data without the need to remember any access code.
Amongst them, fingerprint sensors are the most widespread because they seem to
provide a go... | computer science |
30,587 | Learning Fixation Point Strategy for Object Detection and Classification | cs.CV | We propose a novel recurrent attentional structure to localize and recognize
objects jointly. The network can learn to extract a sequence of local
observations with detailed appearance and rough context, instead of sliding
windows or convolutions on the entire image. Meanwhile, those observations are
fused to complete ... | computer science |
30,588 | On the Evaluation of Video Keyframe Summaries using User Ground Truth | cs.CV | Given the great interest in creating keyframe summaries from video, it is
surprising how little has been done to formalise their evaluation and
comparison. User studies are often carried out to demonstrate that a proposed
method generates a more appealing summary than one or two rival methods. But
larger comparison stu... | computer science |
30,589 | Cross-language Framework for Word Recognition and Spotting of Indic
Scripts | cs.CV | Handwritten word recognition and spotting of low-resource scripts are
difficult as sufficient training data is not available and it is often
expensive for collecting data of such scripts. This paper presents a novel
cross language platform for handwritten word recognition and spotting for such
low-resource scripts wher... | computer science |
30,590 | ComboGAN: Unrestrained Scalability for Image Domain Translation | cs.CV | This year alone has seen unprecedented leaps in the area of learning-based
image translation, namely CycleGAN, by Zhu et al. But experiments so far have
been tailored to merely two domains at a time, and scaling them to more would
require an quadratic number of models to be trained. And with two-domain models
taking da... | computer science |
30,591 | Bipartite Graph Matching for Keyframe Summary Evaluation | cs.CV | A keyframe summary, or "static storyboard", is a collection of frames from a
video designed to summarise its semantic content. Many algorithms have been
proposed to extract such summaries automatically. How best to evaluate these
outputs is an important but little-discussed question. We review the current
methods for m... | computer science |
30,592 | Scale-Space Anisotropic Total Variation for Limited Angle Tomography | cs.CV | This paper addresses streak reduction in limited angle tomography. Although
the iterative reweighted total variation (wTV) algorithm reduces small streaks
well, it is rather inept at eliminating large ones since total variation (TV)
regularization is scale-dependent and may regard these streaks as homogeneous
areas. He... | computer science |
30,593 | Learning with Imprinted Weights | cs.CV | Human vision is able to immediately recognize novel visual categories after
seeing just one or a few training examples. We describe how to add a similar
capability to ConvNet classifiers by directly setting the final layer weights
from novel training examples during low-shot learning. We call this process
weight imprin... | computer science |
30,594 | Real-time deep hair matting on mobile devices | cs.CV | Augmented reality is an emerging technology in many application domains.
Among them is the beauty industry, where live virtual try-on of beauty products
is of great importance. In this paper, we address the problem of live hair
color augmentation. To achieve this goal, hair needs to be segmented quickly
and accurately.... | computer science |
30,595 | Deep Regression Forests for Age Estimation | cs.CV | Age estimation from facial images is typically cast as a nonlinear regression
problem. The main challenge of this problem is the facial feature space w.r.t.
ages is heterogeneous, due to the large variation in facial appearance across
different persons of the same age and the non-stationary property of aging
patterns. ... | computer science |
30,596 | FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds | cs.CV | Recent deep networks that directly handle points in a point set, e.g.,
PointNet, have been state-of-the-art for supervised semantic learning tasks on
point clouds such as classification and segmentation. In this work, a novel
end-to-end deep auto-encoder is proposed to address unsupervised learning
challenges on point ... | computer science |
30,597 | Learning Sight from Sound: Ambient Sound Provides Supervision for Visual
Learning | cs.CV | The sound of crashing waves, the roar of fast-moving cars -- sound conveys
important information about the objects in our surroundings. In this work, we
show that ambient sounds can be used as a supervisory signal for learning
visual models. To demonstrate this, we train a convolutional neural network to
predict a stat... | computer science |
30,598 | LVreID: Person Re-Identification with Long Sequence Videos | cs.CV | This paper mainly establishes a large-scale Long sequence Video database for
person re-IDentification (LVreID). Different from existing datasets, LVreID
presents many important new features. (1) long sequences: the average sequence
length is 200 frames, which convey more abundant cues like pose and viewpoint
changes th... | computer science |
30,599 | Lost in Time: Temporal Analytics for Long-Term Video Surveillance | cs.CV | Video surveillance is a well researched area of study with substantial work
done in the aspects of object detection, tracking and behavior analysis. With
the abundance of video data captured over a long period of time, we can
understand patterns in human behavior and scene dynamics through data-driven
temporal analytic... | computer science |
30,600 | On the Diversity of Realistic Image Synthesis | cs.CV | Many image processing tasks can be formulated as translating images between
two image domains, such as colorization, super resolution and conditional image
synthesis. In most of these tasks, an input image may correspond to multiple
outputs. However, current existing approaches only show very minor diversity of
the out... | computer science |
30,601 | DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme
Exposure Image Pairs | cs.CV | We present a novel deep learning architecture for fusing static
multi-exposure images. Current multi-exposure fusion (MEF) approaches use
hand-crafted features to fuse input sequence. However, the weak hand-crafted
representations are not robust to varying input conditions. Moreover, they
perform poorly for extreme exp... | computer science |
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