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30,702 | Panoptic Segmentation | cs.CV | We propose and study a novel 'Panoptic Segmentation' (PS) task. Panoptic
segmentation unifies the traditionally distinct tasks of instance segmentation
(detect and segment each object instance) and semantic segmentation (assign a
class label to each pixel). The unification is natural and presents novel
algorithmic chal... | computer science |
30,703 | A Novel Feature Descriptor for Image Retrieval by Combining Modified
Color Histogram and Diagonally Symmetric Co-occurrence Texture Pattern | cs.CV | In this paper, we have proposed a novel feature descriptors combining color
and texture information collectively. In our proposed color descriptor
component, the inter-channel relationship between Hue (H) and Saturation (S)
channels in the HSV color space has been explored which was not done earlier.
We have quantized ... | computer science |
30,704 | Deep convolutional neural networks for segmenting 3D in vivo multiphoton
images of vasculature in Alzheimer disease mouse models | cs.CV | The health and function of tissue rely on its vasculature network to provide
reliable blood perfusion. Volumetric imaging approaches, such as multiphoton
microscopy, are able to generate detailed 3D images of blood vessels that could
contribute to our understanding of the role of vascular structure in normal
physiology... | computer science |
30,705 | Deep Spatial Feature Reconstruction for Partial Person
Re-identification: Alignment-Free Approach | cs.CV | Partial person re-identification (re-id) is a challenging problem, where only
some partial observations (images) of persons are available for matching.
However, few studies have offered a flexible solution of how to identify an
arbitrary patch of a person image. In this paper, we propose a fast and
accurate matching me... | computer science |
30,706 | Recovery of Point Clouds on Surfaces: Application to Image
Reconstruction | cs.CV | We introduce a framework for the recovery of points on a smooth surface in
high-dimensional space, with application to dynamic imaging. We assume the
surface to be the zero-level set of a bandlimited function. We show that the
exponential maps of the points on the surface satisfy annihilation relations,
implying that t... | computer science |
30,707 | Recovery of Noisy Points on Band-limited Surfaces: Kernel Methods
Re-explained | cs.CV | We introduce a continuous domain framework for the recovery of points on a
surface in high dimensional space, represented as the zero-level set of a
bandlimited function. We show that the exponential maps of the points on the
surface satisfy annihilation relations, implying that they lie in a finite
dimensional subspac... | computer science |
30,708 | ScreenerNet: Learning Self-Paced Curriculum for Deep Neural Networks | cs.CV | We propose to learn a curriculum or a syllabus for supervised learning and
deep reinforcement learning with deep neural networks by an attachable deep
neural network, called ScreenerNet. Specifically, we learn a weight for each
sample by jointly training the ScreenerNet and the main network in an
end-to-end self-paced ... | computer science |
30,709 | Instance Embedding Transfer to Unsupervised Video Object Segmentation | cs.CV | We propose a method for unsupervised video object segmentation by
transferring the knowledge encapsulated in image-based instance embedding
networks. The instance embedding network produces an embedding vector for each
pixel that enables identifying all pixels belonging to the same object. Though
trained on static imag... | computer science |
30,710 | Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network
and Polar Transformation | cs.CV | Glaucoma is a chronic eye disease that leads to irreversible vision loss. The
cup to disc ratio (CDR) plays an important role in the screening and diagnosis
of glaucoma. Thus, the accurate and automatic segmentation of optic disc (OD)
and optic cup (OC) from fundus images is a fundamental task. Most existing
methods se... | computer science |
30,711 | Topological Tracking of Connected Components in Image Sequences | cs.CV | Persistent homology provides information about the lifetime of homology
classes along a filtration of cell complexes. Persistence barcode is a
graphical representation of such information. A filtration might be determined
by time in a set of spatiotemporal data, but classical methods for computing
persistent homology d... | computer science |
30,712 | Spot the Difference by Object Detection | cs.CV | In this paper, we propose a simple yet effective solution to a change
detection task that detects the difference between two images, which we call
"spot the difference". Our approach uses CNN-based object detection by stacking
two aligned images as input and considering the differences between the two
images as objects... | computer science |
30,713 | Live Intrinsic Material Estimation | cs.CV | We present the first end-to-end approach for real-time material estimation
for general object shapes that only requires a single color image as input. In
addition to Lambertian surface properties, our approach fully automatically
computes the specular albedo, material shininess, and a foreground
segmentation. We tackle... | computer science |
30,714 | Cooperative Training of Deep Aggregation Networks for RGB-D Action
Recognition | cs.CV | A novel deep neural network training paradigm that exploits the conjoint
information in multiple heterogeneous sources is proposed. Specifically, in a
RGB-D based action recognition task, it cooperatively trains a single
convolutional neural network (named c-ConvNet) on both RGB visual features and
depth features, and ... | computer science |
30,715 | 3D Face Reconstruction with Region Based Best Fit Blending Using Mobile
Phone for Virtual Reality Based Social Media | cs.CV | The use of virtual reality (VR) is exponentially increasing and due to that
many researchers has started to work on developing new VR based social media.
For this purpose it is important to have an avatar of the users which look like
them to be easily generated by the devices which are accessible, such as mobile
phone.... | computer science |
30,716 | Fingerprint Distortion Rectification using Deep Convolutional Neural
Networks | cs.CV | Elastic distortion of fingerprints has a negative effect on the performance
of fingerprint recognition systems. This negative effect brings inconvenience
to users in authentication applications. However, in the negative recognition
scenario where users may intentionally distort their fingerprints, this can be
a serious... | computer science |
30,717 | Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road
Scene Understanding by Convolutional Neural Network | cs.CV | Scene understanding for autonomous vehicles is a challenging computer vision
task, with recent advances in convolutional neural networks (CNNs) achieving
results that notably surpass prior traditional feature driven approaches.
However, limited work investigates the application of such methods either
within the highly ... | computer science |
30,718 | ICFVR 2017: 3rd International Competition on Finger Vein Recognition | cs.CV | In recent years, finger vein recognition has become an important sub-field in
biometrics and been applied to real-world applications. The development of
finger vein recognition algorithms heavily depends on large-scale real-world
data sets. In order to motivate research on finger vein recognition, we
released the large... | computer science |
30,719 | PixelLink: Detecting Scene Text via Instance Segmentation | cs.CV | Most state-of-the-art scene text detection algorithms are deep learning based
methods that depend on bounding box regression and perform at least two kinds
of predictions: text/non-text classification and location regression.
Regression plays a key role in the acquisition of bounding boxes in these
methods, but it is n... | computer science |
30,720 | Semantic Segmentation via Highly Fused Convolutional Network with
Multiple Soft Cost Functions | cs.CV | Semantic image segmentation is one of the most challenged tasks in computer
vision. In this paper, we propose a highly fused convolutional network, which
consists of three parts: feature downsampling, combined feature upsampling and
multiple predictions. We adopt a strategy of multiple steps of upsampling and
combined ... | computer science |
30,721 | Implementation of Deep Convolutional Neural Network in Multi-class
Categorical Image Classification | cs.CV | Convolutional Neural Networks has been implemented in many complex machine
learning takes such as image classification, object identification, autonomous
vehicle and robotic vision tasks. However, ConvNet architecture efficiency and
accuracy depend on a large number of fac- tors. Also, the complex architecture
requires... | computer science |
30,722 | A fully automated framework for lung tumour detection, segmentation and
analysis | cs.CV | Early and correct diagnosis is a very important aspect of cancer treatment.
Detection of tumour in Computed Tomography scan is a tedious and tricky task
which requires expert knowledge and a lot of human working hours. As small
human error is present in any work he does, it is possible that a CT scan could
be misdiagno... | computer science |
30,723 | What have we learned from deep representations for action recognition? | cs.CV | As the success of deep models has led to their deployment in all areas of
computer vision, it is increasingly important to understand how these
representations work and what they are capturing. In this paper, we shed light
on deep spatiotemporal representations by visualizing what two-stream models
have learned in orde... | computer science |
30,724 | ObamaNet: Photo-realistic lip-sync from text | cs.CV | We present ObamaNet, the first architecture that generates both audio and
synchronized photo-realistic lip-sync videos from any new text. Contrary to
other published lip-sync approaches, ours is only composed of fully trainable
neural modules and does not rely on any traditional computer graphics methods.
More precisel... | computer science |
30,725 | Deep Anticipation: Light Weight Intelligent Mobile Sensing in IoT by
Recurrent Architecture | cs.CV | The rapid growth of IoT era is shaping the future of mobile services.
Advanced communication technology enables a heterogeneous connectivity where
mobile devices broadcast information to everything. Mobile applications such as
robotics and vehicles connecting to cloud and surroundings transfer the
short-range on-board ... | computer science |
30,726 | IMU2Face: Real-time Gesture-driven Facial Reenactment | cs.CV | We present IMU2Face, a gesture-driven facial reenactment system. To this end,
we combine recent advances in facial motion capture and inertial measurement
units (IMUs) to control the facial expressions of a person in a target video
based on intuitive hand gestures. IMUs are omnipresent, since modern
smart-phones, smart... | computer science |
30,727 | 3D Surface-to-Structure Translation using Deep Convolutional Networks | cs.CV | Our demonstration shows a system that estimates internal body structures from
3D surface models using deep convolutional neural networks trained on CT
(computed tomography) images of the human body. To take pictures of structures
inside the body, we need to use a CT scanner or an MRI (Magnetic Resonance
Imaging) scanne... | computer science |
30,728 | Quantifying Translation-Invariance in Convolutional Neural Networks | cs.CV | A fundamental problem in object recognition is the development of image
representations that are invariant to common transformations such as
translation, rotation, and small deformations. There are multiple hypotheses
regarding the source of translation invariance in CNNs. One idea is that
translation invariance is due... | computer science |
30,729 | Low-dose spectral CT reconstruction using L0 image gradient and tensor
dictionary | cs.CV | Spectral computed tomography (CT) has a great superiority in lesion
detection, tissue characterization and material decomposition. To further
extend its potential clinical applications, in this work, we propose an
improved tensor dictionary learning method for low-dose spectral CT
reconstruction with a constraint of im... | computer science |
30,730 | Translation of "Zur Ermittlung eines Objektes aus zwei Perspektiven mit
innerer Orientierung" by Erwin Kruppa (1913) | cs.CV | Erwin Kruppa's 1913 paper, Erwin Kruppa, "Zur Ermittlung eines Objektes aus
zwei Perspektiven mit innerer Orientierung", Sitzungsberichte der
Mathematisch-Naturwissenschaftlichen Kaiserlichen Akademie der Wissenschaften,
Vol. 122 (1913), pp. 1939-1948, which may be translated as "To determine a 3D
object from two persp... | computer science |
30,731 | A Large Dataset for Improving Patch Matching | cs.CV | We propose a new dataset for learning local image descriptors which can be
used for significantly improved patch matching. Our proposed dataset consists
of an order of magnitude more number of scenes, images, and positive and
negative correspondences compared to the currently available Multi-View Stereo
(MVS) dataset f... | computer science |
30,732 | Deep Cross Polarimetric Thermal-to-visible Face Recognition | cs.CV | In this paper, we present a deep coupled learning frame- work to address the
problem of matching polarimetric ther- mal face photos against a gallery of
visible faces. Polariza- tion state information of thermal faces provides the
miss- ing textural and geometrics details in the thermal face im- agery which
exist in vi... | computer science |
30,733 | Plan in 2D, execute in 3D: An augmented reality solution for cup
placement in total hip arthroplasty | cs.CV | Reproducibly achieving proper implant alignment is a critical step in total
hip arthroplasty (THA) procedures that has been shown to substantially affect
patient outcome. In current practice, correct alignment of the acetabular cup
is verified in C-arm X-ray images that are acquired in an anterior-posterior
(AP) view. ... | computer science |
30,734 | On-the-fly Augmented Reality for Orthopaedic Surgery Using a Multi-Modal
Fiducial | cs.CV | Fluoroscopic X-ray guidance is a cornerstone for percutaneous orthopaedic
surgical procedures. However, two-dimensional observations of the
three-dimensional anatomy suffer from the effects of projective simplification.
Consequently, many X-ray images from various orientations need to be acquired
for the surgeon to acc... | computer science |
30,735 | LoopSmart: Smart Visual SLAM Through Surface Loop Closure | cs.CV | We present a visual simultaneous localization and mapping (SLAM) framework of
closing surface loops. It combines both sparse feature matching and dense
surface alignment. Sparse feature matching is used for visual odometry and
globally camera pose fine-tuning when dense loops are detected, while dense
surface alignment... | computer science |
30,736 | Object Referring in Videos with Language and Human Gaze | cs.CV | We investigate the problem of object referring (OR) i.e. to localize a target
object in a visual scene coming with a language description. Humans perceive
the world more as continued video snippets than as static images, and describe
objects not only by their appearance, but also by their temporal-spatial
contexts and ... | computer science |
30,737 | Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and
Bodies | cs.CV | We present a unified deformation model for the markerless capture of multiple
scales of human movement, including facial expressions, body motion, and hand
gestures. An initial model is generated by locally stitching together models of
the individual parts of the human body, which we refer to as the "Frankenstein"
mode... | computer science |
30,738 | Deep learning for word-level handwritten Indic script identification | cs.CV | We propose a novel method that uses convolutional neural networks (CNNs) for
feature extraction. Not just limited to conventional spatial domain
representation, we use multilevel 2D discrete Haar wavelet transform, where
image representations are scaled to a variety of different sizes. These are
then used to train diff... | computer science |
30,739 | VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling | cs.CV | Jointing visual-semantic embeddings (VSE) have become a research hotpot for
the task of image annotation, which suffers from the issue of semantic gap,
i.e., the gap between images' visual features (low-level) and labels' semantic
features (high-level). This issue will be even more challenging if visual
features cannot... | computer science |
30,740 | FOTS: Fast Oriented Text Spotting with a Unified Network | cs.CV | Incidental scene text spotting is considered one of the most difficult and
valuable challenges in the document analysis community. Most existing methods
treat text detection and recognition as separate tasks. In this work, we
propose a unified end-to-end trainable Fast Oriented Text Spotting (FOTS)
network for simultan... | computer science |
30,741 | Accelerated Training for Massive Classification via Dynamic Class
Selection | cs.CV | Massive classification, a classification task defined over a vast number of
classes (hundreds of thousands or even millions), has become an essential part
of many real-world systems, such as face recognition. Existing methods,
including the deep networks that achieved remarkable success in recent years,
were mostly dev... | computer science |
30,742 | Efficient Image Evidence Analysis of CNN Classification Results | cs.CV | Convolutional neural networks (CNNs) define the current state-of-the-art for
image recognition. With their emerging popularity, especially for critical
applications like medical image analysis or self-driving cars, confirmability
is becoming an issue. The black-box nature of trained predictors make it
difficult to trac... | computer science |
30,743 | Moving Vehicle Detection Using AdaBoost and Haar-Like Feature in
Surveillance Videos | cs.CV | Vehicle detection is a technology which its aim is to locate and show the
vehicle size in digital images. In this technology, vehicles are detected in
presence of other things like trees and buildings. It has an important role in
many computer vision applications such as vehicle tracking, analyzing the
traffic scene an... | computer science |
30,744 | Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption | cs.CV | Recent advances in vision tasks (e.g., segmentation) highly depend on the
availability of large-scale real-world image annotations obtained by cumbersome
human labors. Moreover, the perception performance often drops significantly
for new scenarios, due to the poor generalization capability of models trained
on limited... | computer science |
30,745 | Crossing Generative Adversarial Networks for Cross-View Person
Re-identification | cs.CV | Person re-identification (\textit{re-id}) refers to matching pedestrians
across disjoint yet non-overlapping camera views. The most effective way to
match these pedestrians undertaking significant visual variations is to seek
reliably invariant features that can describe the person of interest
faithfully. Most of exist... | computer science |
30,746 | 3D-DETNet: a Single Stage Video-Based Vehicle Detector | cs.CV | Video-based vehicle detection has received considerable attention over the
last ten years and there are many deep learning based detection methods which
can be applied to it. However, these methods are devised for still images and
applying them for video vehicle detection directly always obtains poor
performance. In th... | computer science |
30,747 | Learning Implicit Brain MRI Manifolds with Deep Learning | cs.CV | An important task in image processing and neuroimaging is to extract
quantitative information from the acquired images in order to make observations
about the presence of disease or markers of development in populations. Having
a lowdimensional manifold of an image allows for easier statistical comparisons
between grou... | computer science |
30,748 | Hi-Fi: Hierarchical Feature Integration for Skeleton Detection | cs.CV | In natural images, the scales (thickness) of object skeletons may
dramatically vary among objects and object parts. Thus, robust skeleton
detection requires powerful multi-scale feature integration ability. To address
this issue, we present a new convolutional neural network (CNN) architecture by
introducing a novel hi... | computer science |
30,749 | Improved Style Transfer by Respecting Inter-layer Correlations | cs.CV | A popular series of style transfer methods apply a style to a content image
by controlling mean and covariance of values in early layers of a feature
stack. This is insufficient for transferring styles that have strong structure
across spatial scales like, e.g., textures where dots lie on long curves. This
paper demons... | computer science |
30,750 | Domain-Specific Face Synthesis for Video Face Recognition from a Single
Sample Per Person | cs.CV | The performance of still-to-video face recognition (FR) systems can decline
significantly because faces captured in the unconstrained operational domain
(OD) have a different underlying data distribution compared to faces captured
under controlled conditions in the enrollment domain (ED). This is particularly
true when... | computer science |
30,751 | Learning Hierarchical Features for Visual Object Tracking with Recursive
Neural Networks | cs.CV | Recently, deep learning has achieved very promising results in visual object
tracking. Deep neural networks in existing tracking methods require a lot of
training data to learn a large number of parameters. However, training data is
not sufficient for visual object tracking as annotations of a target object are
only av... | computer science |
30,752 | ReMotENet: Efficient Relevant Motion Event Detection for Large-scale
Home Surveillance Videos | cs.CV | This paper addresses the problem of detecting relevant motion caused by
objects of interest (e.g., person and vehicles) in large scale home
surveillance videos. The traditional method usually consists of two separate
steps, i.e., detecting moving objects with background subtraction running on
the camera, and filtering ... | computer science |
30,753 | Improving utility of brain tumor confocal laser endomicroscopy:
objective value assessment and diagnostic frame detection with convolutional
neural networks | cs.CV | Confocal laser endomicroscopy (CLE), although capable of obtaining images at
cellular resolution during surgery of brain tumors in real time, creates as
many non-diagnostic as diagnostic images. Non-useful images are often distorted
due to relative motion between probe and brain or blood artifacts. Many images,
however... | computer science |
30,754 | SBNet: Sparse Blocks Network for Fast Inference | cs.CV | Conventional deep convolutional neural networks (CNNs) apply convolution
operators uniformly in space across all feature maps for hundreds of layers -
this incurs a high computational cost for real time applications. For many
problems such as object detection and semantic segmentation, we are able to
obtain a low-cost ... | computer science |
30,755 | Architecture Based Classification of Leaf Images | cs.CV | Plant classification and identification has so far been an important and
difficult task. In this paper, an efficient and systematic approach for
extracting the leaf architecture characters from captured digital images is
proposed. The input image is first pre-processed in five steps to be prepared
for feature extractio... | computer science |
30,756 | Foreground Segmentation Using a Triplet Convolutional Neural Network for
Multiscale Feature Encoding | cs.CV | A common approach for moving objects segmentation in a scene is to perform a
background subtraction. Several methods have been proposed in this domain.
However, they lack the ability of handling various difficult scenarios such as
illumination changes, background or camera motion, camouflage effect, shadow
etc. To addr... | computer science |
30,757 | Identity-preserving Face Recovery from Portraits | cs.CV | Recovering the latent photorealistic faces from their artistic portraits aids
human perception and facial analysis. However, a recovery process that can
preserve identity is challenging because the fine details of real faces can be
distorted or lost in stylized images. In this paper, we present a new
Identity-preservin... | computer science |
30,758 | Long-term Multi-granularity Deep Framework for Driver Drowsiness
Detection | cs.CV | For real-world driver drowsiness detection from videos, the variation of head
pose is so large that the existing methods on global face is not capable of
extracting effective features, such as looking aside and lowering head.
Temporal dependencies with variable length are also rarely considered by the
previous approach... | computer science |
30,759 | Synthetic Data Augmentation using GAN for Improved Liver Lesion
Classification | cs.CV | In this paper, we present a data augmentation method that generates synthetic
medical images using Generative Adversarial Networks (GANs). We propose a
training scheme that first uses classical data augmentation to enlarge the
training set and then further enlarges the data size and its diversity by
applying GAN techni... | computer science |
30,760 | Deep Crisp Boundaries: From Boundaries to Higher-level Tasks | cs.CV | Edge detection has made significant progress with the help of deep
Convolutional Networks (ConvNet). ConvNet based edge detectors approached human
level performance on standard benchmarks. We provide a systematical study of
these detector outputs, and show that they failed to accurately localize edges,
which can be adv... | computer science |
30,761 | Ensemble One-dimensional Convolution Neural Networks for Skeleton-based
Action Recognition | cs.CV | In this paper, we proposed a effective but extensible residual
one-dimensional convolution neural network as base network, based on the this
network, we proposed four subnets to explore the features of skeleton sequences
from each aspect. Given a skeleton sequences, the spatial information are
encoded into the skeleton... | computer science |
30,762 | Facial Attributes: Accuracy and Adversarial Robustness | cs.CV | Facial attributes, emerging soft biometrics, must be automatically and
reliably extracted from images in order to be usable in stand-alone systems.
While recent methods extract facial attributes using deep neural networks
(DNNs) trained on labeled facial attribute data, the robustness of deep
attribute representations ... | computer science |
30,763 | Bridging the Gap: Simultaneous Fine Tuning for Data Re-Balancing | cs.CV | There are many real-world classification problems wherein the issue of data
imbalance (the case when a data set contains substantially more samples for
one/many classes than the rest) is unavoidable. While under-sampling the
problematic classes is a common solution, this is not a compelling option when
the large data c... | computer science |
30,764 | End-to-end detection-segmentation network with ROI convolution | cs.CV | We propose an end-to-end neural network that improves the segmentation
accuracy of fully convolutional networks by incorporating a localization unit.
This network performs object localization first, which is then used as a cue to
guide the training of the segmentation network. We test the proposed method on
a segmentat... | computer science |
30,765 | SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis | cs.CV | Synthesizing realistic images from human drawn sketches is a challenging
problem in computer graphics and vision. Existing approaches either need exact
edge maps, or require a database to retrieve images from. In this work, we
propose a novel Generative Adversarial Network (GAN) approach that synthesizes
realistic look... | computer science |
30,766 | TextBoxes++: A Single-Shot Oriented Scene Text Detector | cs.CV | Scene text detection is an important step of scene text recognition system
and also a challenging problem. Different from general object detection, the
main challenges of scene text detection lie on arbitrary orientations, small
sizes, and significantly variant aspect ratios of text in natural images. In
this paper, we... | computer science |
30,767 | Adversarial Spheres | cs.CV | State of the art computer vision models have been shown to be vulnerable to
small adversarial perturbations of the input. In other words, most images in
the data distribution are both correctly classified by the model and are very
close to a visually similar misclassified image. Despite substantial research
interest, t... | computer science |
30,768 | CANDY: Conditional Adversarial Networks based Fully End-to-End System
for Single Image Haze Removal | cs.CV | Single image haze removal is a very challenging and ill-posed problem. The
existing haze removal methods in literature, including the recently introduced
deep learning methods, model the problem of haze removal as that of estimating
intermediate parameters, viz., scene transmission map and atmospheric light.
These are ... | computer science |
30,769 | DeepStyle: Multimodal Search Engine for Fashion and Interior Design | cs.CV | In this paper, we propose a multimodal search engine that combines visual and
textual cues to retrieve items from a multimedia database aesthetically similar
to the query. The goal of our engine is to enable intuitive retrieval of
fashion merchandise such as clothes or furniture. Existing search engines treat
textual i... | computer science |
30,770 | Recognizing Material Properties from Images | cs.CV | Humans rely on properties of the materials that make up objects to guide our
interactions with them. Grasping smooth materials, for example, requires care,
and softness is an ideal property for fabric used in bedding. Even when these
properties are not visual (e.g. softness is a physical property), we may still
infer t... | computer science |
30,771 | Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised
Object Detection | cs.CV | Deep CNN-based object detection systems have achieved remarkable success on
several large-scale object detection benchmarks. However, training such
detectors requires a large number of labeled bounding boxes, which are more
difficult to obtain than image-level annotations. Previous work addresses this
issue by transfor... | computer science |
30,772 | An overview of deep learning based methods for unsupervised and
semi-supervised anomaly detection in videos | cs.CV | Videos represent the primary source of information for surveillance
applications and are available in large amounts but in most cases contain
little or no annotation for supervised learning. This article reviews the
state-of-the-art deep learning based methods for video anomaly detection and
categorizes them based on t... | computer science |
30,773 | A Benchmark for Breast Ultrasound Image Segmentation (BUSIS) | cs.CV | Breast ultrasound (BUS) image segmentation is challenging and critical for
BUS Computer-Aided Diagnosis (CAD) systems. Many BUS segmentation approaches
have been proposed in the last two decades, but the performances of most
approaches have been assessed using relatively small private datasets with
differ-ent quantitat... | computer science |
30,774 | FWLBP: A Scale Invariant Descriptor for Texture Classification | cs.CV | In this paper we propose a novel texture recognition feature called Fractal
Weighted Local Binary Pattern (FWLBP). It has been observed that fractal
dimension (FD) measure is relatively invariant to scale-changes, and presents a
good correlation with human perception of surface roughness. We have utilized
this property... | computer science |
30,775 | Instance Map based Image Synthesis with a Denoising Generative
Adversarial Network | cs.CV | Semantic layouts based Image synthesizing, which has benefited from the
success of Generative Adversarial Network (GAN), has drawn much attention in
these days. How to enhance the synthesis image equality while keeping the
stochasticity of the GAN is still a challenge. We propose a novel denoising
framework to handle t... | computer science |
30,776 | Simultaneous Tensor Completion and Denoising by Noise Inequality
Constrained Convex Optimization | cs.CV | Tensor completion is a technique of filling missing elements of the
incomplete data tensors. It being actively studied based on the convex
optimization scheme such as nuclear-norm minimization. When given data tensors
include some noises, the nuclear-norm minimization problem is usually converted
to the nuclear-norm `r... | computer science |
30,777 | Unsupervised Despeckling | cs.CV | Contrast and quality of ultrasound images are adversely affected by the
excessive presence of speckle. However, being an inherent imaging property,
speckle helps in tissue characterization and tracking. Thus, despeckling of the
ultrasound images requires the reduction of speckle extent without any
oversmoothing. In thi... | computer science |
30,778 | Deep Supervision with Intermediate Concepts | cs.CV | Recent data-driven approaches to scene interpretation predominantly pose
inference as an end-to-end black-box mapping, commonly performed by a
Convolutional Neural Network (CNN). However, decades of work on perceptual
organization in both human and machine vision suggests that there are often
intermediate representatio... | computer science |
30,779 | Inferring a Third Spatial Dimension from 2D Histological Images | cs.CV | Histological images are obtained by transmitting light through a tissue
specimen that has been stained in order to produce contrast. This process
results in 2D images of the specimen that has a three-dimensional structure. In
this paper, we propose a method to infer how the stains are distributed in the
direction perpe... | computer science |
30,780 | Unsupervised Real-to-Virtual Domain Unification for End-to-End Highway
Driving | cs.CV | In the spectrum of vision-based autonomous driving, vanilla end-to-end models
are not interpretable and suboptimal in performance, while mediated perception
models require additional intermediate representations such as segmentation
masks or detection bounding boxes, whose annotation can be prohibitively
expensive as w... | computer science |
30,781 | Multi-Scale Attention with Dense Encoder for Handwritten Mathematical
Expression Recognition | cs.CV | Handwritten mathematical expression recognition is a challenging problem due
to the complicated two-dimensional structures, ambiguous handwriting input and
variant scales of handwritten math symbols. To settle this problem, we utilize
the attention based encoder-decoder model that recognizes mathematical
expression ima... | computer science |
30,782 | Segment-based Methods for Facial Attribute Detection from Partial Faces | cs.CV | State-of-the-art methods of attribute detection from faces almost always
assume the presence of a full, unoccluded face. Hence, their performance
degrades for partially visible and occluded faces. In this paper, we introduce
SPLITFACE, a deep convolutional neural network-based method that is explicitly
designed to perf... | computer science |
30,783 | From Superpixel to Human Shape Modelling for Carried Object Detection | cs.CV | Detecting carried objects is one of the requirements for developing systems
to reason about activities involving people and objects. We present an approach
to detect carried objects from a single video frame with a novel method that
incorporates features from multiple scales. Initially, a foreground mask in a
video fra... | computer science |
30,784 | Soft Locality Preserving Map (SLPM) for Facial Expression Recognition | cs.CV | For image recognition, an extensive number of methods have been proposed to
overcome the high-dimensionality problem of feature vectors being used. These
methods vary from unsupervised to supervised, and from statistics to
graph-theory based. In this paper, the most popular and the state-of-the-art
methods for dimensio... | computer science |
30,785 | Multi-view Consistency as Supervisory Signal for Learning Shape and Pose
Prediction | cs.CV | We present a framework for learning single-view shape and pose prediction
without using direct supervision for either. Our approach allows leveraging
multi-view observations from unknown poses as supervisory signal during
training. Our proposed training setup enforces geometric consistency between
the independently pre... | computer science |
30,786 | Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low
Resolution Action Recognition | cs.CV | A major emerging challenge is how to protect people's privacy as cameras and
computer vision are increasingly integrated into our daily lives, including in
smart devices inside homes. A potential solution is to capture and record just
the minimum amount of information needed to perform a task of interest. In this
paper... | computer science |
30,787 | Multi-Task Spatiotemporal Neural Networks for Structured Surface
Reconstruction | cs.CV | Deep learning methods have surpassed the performance of traditional
techniques on a wide range of problems in computer vision, but nearly all of
this work has studied consumer photos, where precisely correct output is often
not critical. It is less clear how well these techniques may apply on
structured prediction prob... | computer science |
30,788 | Non-Rigid Image Registration Using Self-Supervised Fully Convolutional
Networks without Training Data | cs.CV | A novel non-rigid image registration algorithm is built upon fully
convolutional networks (FCNs) to optimize and learn spatial transformations
between pairs of images to be registered in a self-supervised learning
framework. Different from most existing deep learning based image registration
methods that learn spatial ... | computer science |
30,789 | Brain Age Prediction Based on Resting-State Functional Connectivity
Patterns Using Convolutional Neural Networks | cs.CV | Brain age prediction based on neuroimaging data could help characterize both
the typical brain development and neuropsychiatric disorders. Pattern
recognition models built upon functional connectivity (FC) measures derived
from resting state fMRI (rsfMRI) data have been successfully used to predict
the brain age. Howev... | computer science |
30,790 | Application of a semantic segmentation convolutional neural network for
accurate automatic detection and mapping of solar photovoltaic arrays in
aerial imagery | cs.CV | We consider the problem of automatically detecting small-scale solar
photovoltaic arrays for behind-the-meter energy resource assessment in high
resolution aerial imagery. Such algorithms offer a faster and more
cost-effective solution to collecting information on distributed solar
photovoltaic (PV) arrays, such as the... | computer science |
30,791 | Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture | cs.CV | Deep neural networks have shown excellent performance for stereo matching.
Many efforts focus on the feature extraction and similarity measurement of the
matching cost computation step while less attention is paid on cost aggregation
which is crucial for stereo matching. In this paper, we present a
learning-based cost ... | computer science |
30,792 | How should a fixed budget of dwell time be spent in scanning electron
microscopy to optimize image quality? | cs.CV | In scanning electron microscopy, the achievable image quality is often
limited by a maximum feasible acquisition time per dataset. Particularly with
regard to three-dimensional or large field-of-view imaging, a compromise must
be found between a high amount of shot noise, which leads to a low
signal-to-noise ratio, and... | computer science |
30,793 | Hierarchical Motion Consistency Constraint for Efficient Geometrical
Verification in UAV Image Matching | cs.CV | This paper proposes a strategy for efficient geometrical verification in
unmanned aerial vehicle (UAV) image matching. First, considering the complex
transformation model between correspondence set in the image-space, feature
points of initial candidate matches are projected onto an elevation plane in
the object-space,... | computer science |
30,794 | Generative Single Image Reflection Separation | cs.CV | Single image reflection separation is an ill-posed problem since two scenes,
a transmitted scene and a reflected scene, need to be inferred from a single
observation. To make the problem tractable, in this work we assume that
categories of two scenes are known. It allows us to address the problem by
generating both sce... | computer science |
30,795 | QuickNAT: Segmenting MRI Neuroanatomy in 20 seconds | cs.CV | Whole brain segmentation from structural magnetic resonance imaging is a
prerequisite for most morphological analyses, but requires hours of processing
time and therefore delays the availability of image markers after scan
acquisition. We introduce QuickNAT, a fully convolution neural network that
segments a brain scan... | computer science |
30,796 | MSDNN: Multi-Scale Deep Neural Network for Salient Object Detection | cs.CV | Salient object detection is a fundamental problem and has been received a
great deal of attentions in computer vision. Recently deep learning model
became a powerful tool for image feature extraction. In this paper, we propose
a multi-scale deep neural network (MSDNN) for salient object detection. The
proposed model fi... | computer science |
30,797 | Deep saliency: What is learnt by a deep network about saliency? | cs.CV | Deep convolutional neural networks have achieved impressive performance on a
broad range of problems, beating prior art on established benchmarks, but it
often remains unclear what are the representations learnt by those systems and
how they achieve such performance. This article examines the specific problem
of salien... | computer science |
30,798 | Real-world Anomaly Detection in Surveillance Videos | cs.CV | Surveillance videos are able to capture a variety of realistic anomalies. In
this paper, we propose to learn anomalies by exploiting both normal and
anomalous videos. To avoid annotating the anomalous segments or clips in
training videos, which is very time consuming, we propose to learn anomaly
through the deep multip... | computer science |
30,799 | Light Field Super-Resolution using a Low-Rank Prior and Deep
Convolutional Neural Networks | cs.CV | Light field imaging has recently known a regain of interest due to the
availability of practical light field capturing systems that offer a wide range
of applications in the field of computer vision. However, capturing
high-resolution light fields remains technologically challenging since the
increase in angular resolu... | computer science |
30,800 | Prototypicality effects in global semantic description of objects | cs.CV | We propose a new approach to face the semantic features descriptions of
objects based in the prototypicality effects of prototypes theory. Our
descriptor, called global semantic descriptor, is capable of coding and storing
a semantic (central and peripheral) meaning of object. Our model compute the
semantic prototype o... | computer science |
30,801 | TieNet: Text-Image Embedding Network for Common Thorax Disease
Classification and Reporting in Chest X-rays | cs.CV | Chest X-rays are one of the most common radiological examinations in daily
clinical routines. Reporting thorax diseases using chest X-rays is often an
entry-level task for radiologist trainees. Yet, reading a chest X-ray image
remains a challenging job for learning-oriented machine intelligence, due to
(1) shortage of ... | computer science |
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