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24,002 | Template Matching with Deformable Diversity Similarity | cs.CV | We propose a novel measure for template matching named Deformable Diversity
Similarity -- based on the diversity of feature matches between a target image
window and the template. We rely on both local appearance and geometric
information that jointly lead to a powerful approach for matching. Our key
contribution is a ... | computer science |
24,003 | A Functional Regression approach to Facial Landmark Tracking | cs.CV | Linear regression is a fundamental building block in many face detection and
tracking algorithms, typically used to predict shape displacements from image
features through a linear mapping. This paper presents a Functional Regression
solution to the least squares problem, which we coin Continuous Regression,
resulting ... | computer science |
24,004 | Embedded Line Scan Image Sensors: The Low Cost Alternative for High
Speed Imaging | cs.CV | In this paper we propose a low-cost high-speed imaging line scan system. We
replace an expensive industrial line scan camera and illumination with a
custom-built set-up of cheap off-the-shelf components, yielding a measurement
system with comparative quality while costing about 20 times less. We use a
low-cost linear (... | computer science |
24,005 | Process Monitoring of Extrusion Based 3D Printing via Laser Scanning | cs.CV | Extrusion based 3D Printing (E3DP) is an Additive Manufacturing (AM)
technique that extrudes thermoplastic polymer in order to build up components
using a layerwise approach. Hereby, AM typically requires long production times
in comparison to mass production processes such as Injection Molding. Failures
during the AM ... | computer science |
24,006 | Exploring the potential of combining time of flight and thermal infrared
cameras for person detection | cs.CV | Combining new, low-cost thermal infrared and time-of-flight range sensors
provides new opportunities. In this position paper we explore the possibilities
of combining these sensors and using their fused data for person detection. The
proposed calibration approach for this sensor combination differs from the
traditional... | computer science |
24,007 | Global Hypothesis Generation for 6D Object Pose Estimation | cs.CV | This paper addresses the task of estimating the 6D pose of a known 3D object
from a single RGB-D image. Most modern approaches solve this task in three
steps: i) Compute local features; ii) Generate a pool of pose-hypotheses; iii)
Select and refine a pose from the pool. This work focuses on the second step.
While all e... | computer science |
24,008 | Pano2Vid: Automatic Cinematography for Watching 360$^{\circ}$ Videos | cs.CV | We introduce the novel task of Pano2Vid $-$ automatic cinematography in
panoramic 360$^{\circ}$ videos. Given a 360$^{\circ}$ video, the goal is to
direct an imaginary camera to virtually capture natural-looking normal
field-of-view (NFOV) video. By selecting "where to look" within the panorama at
each time step, Pano2... | computer science |
24,009 | Differential Angular Imaging for Material Recognition | cs.CV | Material recognition for real-world outdoor surfaces has become increasingly
important for computer vision to support its operation "in the wild."
Computational surface modeling that underlies material recognition has
transitioned from reflectance modeling using in-lab controlled radiometric
measurements to image-based... | computer science |
24,010 | Automatic Detection of ADHD and ASD from Expressive Behaviour in RGBD
Data | cs.CV | Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder
(ASD) are neurodevelopmental conditions which impact on a significant number of
children and adults. Currently, the diagnosis of such disorders is done by
experts who employ standard questionnaires and look for certain behavioural
markers thro... | computer science |
24,011 | DeMoN: Depth and Motion Network for Learning Monocular Stereo | cs.CV | In this paper we formulate structure from motion as a learning problem. We
train a convolutional network end-to-end to compute depth and camera motion
from successive, unconstrained image pairs. The architecture is composed of
multiple stacked encoder-decoder networks, the core part being an iterative
network that is a... | computer science |
24,012 | Research on the Multiple Feature Fusion Image Retrieval Algorithm based
on Texture Feature and Rough Set Theory | cs.CV | Recently, we have witnessed the explosive growth of images with complex
information and content. In order to effectively and precisely retrieve desired
images from a large-scale image database with low time-consuming, we propose
the multiple feature fusion image retrieval algorithm based on the texture
feature and roug... | computer science |
24,013 | Complex Matrix Factorization for Face Recognition | cs.CV | This work developed novel complex matrix factorization methods for face
recognition; the methods were complex matrix factorization (CMF), sparse
complex matrix factorization (SpaCMF), and graph complex matrix factorization
(GraCMF). After real-valued data are transformed into a complex field, the
complex-valued matrix ... | computer science |
24,014 | An Efficient Algorithm for the Piecewise-Smooth Model with Approximately
Explicit Solutions | cs.CV | This paper presents an efficient approach to image segmentation that
approximates the piecewise-smooth (PS) functional in [12] with explicit
solutions. By rendering some rational constraints on the initial conditions and
the final solutions of the PS functional, we propose two novel formulations
which can be approximat... | computer science |
24,015 | Contextual Visual Similarity | cs.CV | Measuring visual similarity is critical for image understanding. But what
makes two images similar? Most existing work on visual similarity assumes that
images are similar because they contain the same object instance or category.
However, the reason why images are similar is much more complex. For example,
from the pe... | computer science |
24,016 | Query-adaptive Image Retrieval by Deep Weighted Hashing | cs.CV | Hashing methods have attracted much attention for large scale image
retrieval. Some deep hashing methods have achieved promising results by taking
advantage of the strong representation power of deep networks recently.
However, existing deep hashing methods treat all hash bits equally. On one
hand, a large number of im... | computer science |
24,017 | AGA: Attribute Guided Augmentation | cs.CV | We consider the problem of data augmentation, i.e., generating artificial
samples to extend a given corpus of training data. Specifically, we propose
attributed-guided augmentation (AGA) which learns a mapping that allows to
synthesize data such that an attribute of a synthesized sample is at a desired
value or strengt... | computer science |
24,018 | Classification of Neurological Gait Disorders Using Multi-task Feature
Learning | cs.CV | As our population ages, neurological impairments and degeneration of the
musculoskeletal system yield gait abnormalities, which can significantly reduce
quality of life. Gait rehabilitative therapy has been widely adopted to help
patients maximize community participation and living independence. To further
improve the ... | computer science |
24,019 | Filter sharing: Efficient learning of parameters for volumetric
convolutions | cs.CV | Typical convolutional neural networks (CNNs) have several millions of
parameters and require a large amount of annotated data to train them. In
medical applications where training data is hard to come by, these
sophisticated machine learning models are difficult to train. In this paper, we
propose a method to reduce th... | computer science |
24,020 | From Motion Blur to Motion Flow: a Deep Learning Solution for Removing
Heterogeneous Motion Blur | cs.CV | Removing pixel-wise heterogeneous motion blur is challenging due to the
ill-posed nature of the problem. The predominant solution is to estimate the
blur kernel by adding a prior, but the extensive literature on the subject
indicates the difficulty in identifying a prior which is suitably informative,
and general. Rath... | computer science |
24,021 | Scene Flow Estimation: A Survey | cs.CV | This paper is the first to review the scene flow estimation field, which
analyzes and compares methods, technical challenges, evaluation methodologies
and performance of scene flow estimation. Existing algorithms are categorized
in terms of scene representation, data source, and calculation scheme, and the
pros and con... | computer science |
24,022 | Progressive Tree-like Curvilinear Structure Reconstruction with
Structured Ranking Learning and Graph Algorithm | cs.CV | We propose a novel tree-like curvilinear structure reconstruction algorithm
based on supervised learning and graph theory. In this work we analyze image
patches to obtain the local major orientations and the rankings that correspond
to the curvilinear structure. To extract local curvilinear features, we compute
oriente... | computer science |
24,023 | Learning Video Object Segmentation from Static Images | cs.CV | Inspired by recent advances of deep learning in instance segmentation and
object tracking, we introduce video object segmentation problem as a concept of
guided instance segmentation. Our model proceeds on a per-frame basis, guided
by the output of the previous frame towards the object of interest in the next
frame. We... | computer science |
24,024 | FCNs in the Wild: Pixel-level Adversarial and Constraint-based
Adaptation | cs.CV | Fully convolutional models for dense prediction have proven successful for a
wide range of visual tasks. Such models perform well in a supervised setting,
but performance can be surprisingly poor under domain shifts that appear mild
to a human observer. For example, training on one city and testing on another
in a diff... | computer science |
24,025 | Domain knowledge assisted cyst segmentation in OCT retinal images | cs.CV | 3D imaging modalities are becoming increasingly popular and relevant in
retinal imaging owing to their effectiveness in highlighting structures in
sub-retinal layers. OCT is one such modality which has great importance in the
context of analysis of cystoid structures in subretinal layers. Signal to noise
ratio(SNR) of ... | computer science |
24,026 | Deep Supervision with Shape Concepts for Occlusion-Aware 3D Object
Parsing | cs.CV | Monocular 3D object parsing is highly desirable in various scenarios
including occlusion reasoning and holistic scene interpretation. We present a
deep convolutional neural network (CNN) architecture to localize semantic parts
in 2D image and 3D space while inferring their visibility states, given a
single RGB image. O... | computer science |
24,027 | Predicting Ground-Level Scene Layout from Aerial Imagery | cs.CV | We introduce a novel strategy for learning to extract semantically meaningful
features from aerial imagery. Instead of manually labeling the aerial imagery,
we propose to predict (noisy) semantic features automatically extracted from
co-located ground imagery. Our network architecture takes an aerial image as
input, ex... | computer science |
24,028 | Joint Hand Detection and Rotation Estimation by Using CNN | cs.CV | Hand detection is essential for many hand related tasks, e.g. parsing hand
pose, understanding gesture, which are extremely useful for robotics and
human-computer interaction. However, hand detection in uncontrolled
environments is challenging due to the flexibility of wrist joint and cluttered
background. We propose a... | computer science |
24,029 | A Maximum A Posteriori Estimation Framework for Robust High Dynamic
Range Video Synthesis | cs.CV | High dynamic range (HDR) image synthesis from multiple low dynamic range
(LDR) exposures continues to be actively researched. The extension to HDR video
synthesis is a topic of significant current interest due to potential cost
benefits. For HDR video, a stiff practical challenge presents itself in the
form of accurate... | computer science |
24,030 | Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation | cs.CV | Learning from weakly-supervised data is one of the main challenges in machine
learning and computer vision, especially for tasks such as image semantic
segmentation where labeling is extremely expensive and subjective. In this
paper, we propose a novel neural network architecture to perform
weakly-supervised learning b... | computer science |
24,031 | Deep TEN: Texture Encoding Network | cs.CV | We propose a Deep Texture Encoding Network (Deep-TEN) with a novel Encoding
Layer integrated on top of convolutional layers, which ports the entire
dictionary learning and encoding pipeline into a single model. Current methods
build from distinct components, using standard encoders with separate
off-the-shelf features ... | computer science |
24,032 | Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment | cs.CV | This paper presents a novel algorithm that utilizes a 2D floorplan to align
panorama RGBD scans. While effective panorama RGBD alignment techniques exist,
such a system requires extremely dense RGBD image sampling. Our approach can
significantly reduce the number of necessary scans with the aid of a floorplan
image. We... | computer science |
24,033 | Fast Fourier single-pixel imaging using binary illumination | cs.CV | Fourier single-pixel imaging (FSI) has proven capable of reconstructing
high-quality two-dimensional and three-dimensional images. The utilization of
the sparsity of natural images in Fourier domain allows high-resolution images
to be reconstructed from far fewer measurements than effective image pixels.
However, apply... | computer science |
24,034 | Gesture-based Bootstrapping for Egocentric Hand Segmentation | cs.CV | Accurately identifying hands in images is a key sub-task for human activity
understanding with wearable first-person point-of-view cameras. Traditional
hand segmentation approaches rely on a large corpus of manually labeled data to
generate robust hand detectors. However, these approaches still face challenges
as the a... | computer science |
24,035 | Facial Expression Recognition using Convolutional Neural Networks: State
of the Art | cs.CV | The ability to recognize facial expressions automatically enables novel
applications in human-computer interaction and other areas. Consequently, there
has been active research in this field, with several recent works utilizing
Convolutional Neural Networks (CNNs) for feature extraction and inference.
These works diffe... | computer science |
24,036 | ActionFlowNet: Learning Motion Representation for Action Recognition | cs.CV | Even with the recent advances in convolutional neural networks (CNN) in
various visual recognition tasks, the state-of-the-art action recognition
system still relies on hand crafted motion feature such as optical flow to
achieve the best performance. We propose a multitask learning model
ActionFlowNet to train a single... | computer science |
24,037 | Following Gaze Across Views | cs.CV | Following the gaze of people inside videos is an important signal for
understanding people and their actions. In this paper, we present an approach
for following gaze across views by predicting where a particular person is
looking throughout a scene. We collect VideoGaze, a new dataset which we use as
a benchmark to bo... | computer science |
24,038 | Boundary-aware Instance Segmentation | cs.CV | We address the problem of instance-level semantic segmentation, which aims at
jointly detecting, segmenting and classifying every individual object in an
image. In this context, existing methods typically propose candidate objects,
usually as bounding boxes, and directly predict a binary mask within each such
proposal.... | computer science |
24,039 | Understanding and Mapping Natural Beauty | cs.CV | While natural beauty is often considered a subjective property of images, in
this paper, we take an objective approach and provide methods for quantifying
and predicting the scenicness of an image. Using a dataset containing hundreds
of thousands of outdoor images captured throughout Great Britain with
crowdsourced rat... | computer science |
24,040 | Feature Pyramid Networks for Object Detection | cs.CV | Feature pyramids are a basic component in recognition systems for detecting
objects at different scales. But recent deep learning object detectors have
avoided pyramid representations, in part because they are compute and memory
intensive. In this paper, we exploit the inherent multi-scale, pyramidal
hierarchy of deep ... | computer science |
24,041 | Panoptic Studio: A Massively Multiview System for Social Interaction
Capture | cs.CV | We present an approach to capture the 3D motion of a group of people engaged
in a social interaction. The core challenges in capturing social interactions
are: (1) occlusion is functional and frequent; (2) subtle motion needs to be
measured over a space large enough to host a social group; (3) human appearance
and conf... | computer science |
24,042 | Automatic Lymphocyte Detection in H&E Images with Deep Neural Networks | cs.CV | Automatic detection of lymphocyte in H&E images is a necessary first step in
lots of tissue image analysis algorithms. An accurate and robust automated
lymphocyte detection approach is of great importance in both computer science
and clinical studies. Most of the existing approaches for lymphocyte detection
are based o... | computer science |
24,043 | Co-localization with Category-Consistent CNN Features and Geodesic
Distance Propagation | cs.CV | Co-localization is the problem of localizing objects of the same class using
only the set of images that contain them. This is a challenging task because
the object detector must be built without negative examples that can lead to
more informative supervision signals. The main idea of our method is to cluster
the featu... | computer science |
24,044 | Towards an Automated Image De-fencing Algorithm Using Sparsity | cs.CV | Conventional approaches to image de-fencing suffer from non-robust fence
detection and are limited to processing images of static scenes. In this
position paper, we propose an automatic de-fencing algorithm for images of
dynamic scenes. We divide the problem of image de-fencing into the tasks of
automated fence detecti... | computer science |
24,045 | A Novel Motion Detection Method Resistant to Severe Illumination Changes | cs.CV | Recently, there has been a considerable attention given to the motion
detection problem due to the explosive growth of its applications in video
analysis and surveillance systems. While the previous approaches can produce
good results, an accurate detection of motion remains a challenging task due to
the difficulties r... | computer science |
24,046 | On Choosing Training and Testing Data for Supervised Algorithms in
Ground Penetrating Radar Data for Buried Threat Detection | cs.CV | Ground penetrating radar (GPR) is one of the most popular and successful
sensing modalities that has been investigated for landmine and subsurface
threat detection. Many of the detection algorithms applied to this task are
supervised and therefore require labeled examples of target and non-target data
for training. Tra... | computer science |
24,047 | An Attention-Driven Approach of No-Reference Image Quality Assessment | cs.CV | In this paper, we present a novel method of no-reference image quality
assessment (NR-IQA), which is to predict the perceptual quality score of a
given image without using any reference image. The proposed method harnesses
three functions (i) the visual attention mechanism, which affects many aspects
of visual percepti... | computer science |
24,048 | PIGMIL: Positive Instance Detection via Graph Updating for Multiple
Instance Learning | cs.CV | Positive instance detection, especially for these in positive bags (true
positive instances, TPIs), plays a key role for multiple instance learning
(MIL) arising from a specific classification problem only provided with bag (a
set of instances) label information. However, most previous MIL methods on this
issue ignore ... | computer science |
24,049 | Text-guided Attention Model for Image Captioning | cs.CV | Visual attention plays an important role to understand images and
demonstrates its effectiveness in generating natural language descriptions of
images. On the other hand, recent studies show that language associated with an
image can steer visual attention in the scene during our cognitive process.
Inspired by this, we... | computer science |
24,050 | A Binary Convolutional Encoder-decoder Network for Real-time Natural
Scene Text Processing | cs.CV | In this paper, we develop a binary convolutional encoder-decoder network
(B-CEDNet) for natural scene text processing (NSTP). It converts a text image
to a class-distinguished salience map that reveals the categorical, spatial and
morphological information of characters. The existing solutions are either
memory consumi... | computer science |
24,051 | COCO-Stuff: Thing and Stuff Classes in Context | cs.CV | Semantic classes can be either things (objects with a well-defined shape,
e.g. car, person) or stuff (amorphous background regions, e.g. grass, sky).
While lots of classification and detection works focus on thing classes, less
attention has been given to stuff classes. Nonetheless, stuff classes are
important as they ... | computer science |
24,052 | Hybrid Learning of Optical Flow and Next Frame Prediction to Boost
Optical Flow in the Wild | cs.CV | CNN-based optical flow estimation has attracted attention recently, mainly
due to its impressively high frame rates. These networks perform well on
synthetic datasets, but they are still far behind the classical methods in
real-world videos. This is because there is no ground truth optical flow for
training these netwo... | computer science |
24,053 | PoseAgent: Budget-Constrained 6D Object Pose Estimation via
Reinforcement Learning | cs.CV | State-of-the-art computer vision algorithms often achieve efficiency by
making discrete choices about which hypotheses to explore next. This allows
allocation of computational resources to promising candidates, however, such
decisions are non-differentiable. As a result, these algorithms are hard to
train in an end-to-... | computer science |
24,054 | Deep Supervised Hashing with Triplet Labels | cs.CV | Hashing is one of the most popular and powerful approximate nearest neighbor
search techniques for large-scale image retrieval. Most traditional hashing
methods first represent images as off-the-shelf visual features and then
produce hashing codes in a separate stage. However, off-the-shelf visual
features may not be o... | computer science |
24,055 | 3D fully convolutional networks for subcortical segmentation in MRI: A
large-scale study | cs.CV | This study investigates a 3D and fully convolutional neural network (CNN) for
subcortical brain structure segmentation in MRI. 3D CNN architectures have been
generally avoided due to their computational and memory requirements during
inference. We address the problem via small kernels, allowing deeper
architectures. We... | computer science |
24,056 | Paying More Attention to Attention: Improving the Performance of
Convolutional Neural Networks via Attention Transfer | cs.CV | Attention plays a critical role in human visual experience. Furthermore, it
has recently been demonstrated that attention can also play an important role
in the context of applying artificial neural networks to a variety of tasks
from fields such as computer vision and NLP. In this work we show that, by
properly defini... | computer science |
24,057 | Neural Networks with Manifold Learning for Diabetic Retinopathy
Detection | cs.CV | Widespread outreach programs using remote retinal imaging have proven to
decrease the risk from diabetic retinopathy, the leading cause of blindness in
the US. However, this process still requires manual verification of image
quality and grading of images for level of disease by a trained human grader
and will continue... | computer science |
24,058 | Deep Convolutional Poses for Human Interaction Recognition in Monocular
Videos | cs.CV | Human interaction recognition is a challenging problem in computer vision and
has been researched over the years due to its important applications. With the
development of deep models for the human pose estimation problem, this work
aims to verify the effectiveness of using the human pose in order to recognize
the huma... | computer science |
24,059 | A Fast Keypoint Based Hybrid Method for Copy Move Forgery Detection | cs.CV | Copy move forgery detection in digital images has become a very popular
research topic in the area of image forensics. Due to the availability of
sophisticated image editing tools and ever increasing hardware capabilities, it
has become an easy task to manipulate the digital images. Passive forgery
detection techniques... | computer science |
24,060 | A Video-Based Method for Objectively Rating Ataxia | cs.CV | For many movement disorders, such as Parkinson's disease and ataxia, disease
progression is visually assessed by a clinician using a numerical disease
rating scale. These tests are subjective, time-consuming, and must be
administered by a professional. This can be problematic where specialists are
not available, or whe... | computer science |
24,061 | Spatial Pyramid Convolutional Neural Network for Social Event Detection
in Static Image | cs.CV | Social event detection in a static image is a very challenging problem and
it's very useful for internet of things applications including automatic photo
organization, ads recommender system, or image captioning. Several publications
show that variety of objects, scene, and people can be very ambiguous for the
system t... | computer science |
24,062 | Automated Inference on Sociopsychological Impressions of Attractive
Female Faces | cs.CV | This article is a sequel to our earlier work [25]. The main objective of our
research is to explore the potential of supervised machine learning in
face-induced social computing and cognition, riding on the momentum of much
heralded successes of face processing, analysis and recognition on the tasks of
biometric-based ... | computer science |
24,063 | Compressive Image Recovery Using Recurrent Generative Model | cs.CV | Reconstruction of signals from compressively sensed measurements is an
ill-posed problem. In this paper, we leverage the recurrent generative model,
RIDE, as an image prior for compressive image reconstruction. Recurrent
networks can model long-range dependencies in images and hence are suitable to
handle global multip... | computer science |
24,064 | How do people explore virtual environments? | cs.CV | Understanding how people explore immersive virtual environments is crucial
for many applications, such as designing virtual reality (VR) content,
developing new compression algorithms, or learning computational models of
saliency or visual attention. Whereas a body of recent work has focused on
modeling saliency in des... | computer science |
24,065 | Finding Tiny Faces | cs.CV | Though tremendous strides have been made in object recognition, one of the
remaining open challenges is detecting small objects. We explore three aspects
of the problem in the context of finding small faces: the role of scale
invariance, image resolution, and contextual reasoning. While most recognition
approaches aim ... | computer science |
24,066 | Analysis of proposed PDE-based underwater image enhancement algorithms | cs.CV | This report describes the experimental analysis of proposed underwater image
enhancement algorithms based on partial differential equations (PDEs). The
algorithms perform simultaneous smoothing and enhancement due to the
combination of both processes within the PDE-formulation. The framework enables
the incorporation o... | computer science |
24,067 | Single Image Action Recognition using Semantic Body Part Actions | cs.CV | In this paper, we propose a novel single image action recognition algorithm
which is based on the idea of semantic body part actions. Unlike existing
bottom up methods, we argue that the human action is a combination of
meaningful body part actions. In detail, we divide human body into five parts:
head, torso, arms, ha... | computer science |
24,068 | The Mehler-Fock Transform and some Applications in Texture Analysis and
Color Processing | cs.CV | Many stochastic processes are defined on special geometrical objects like
spheres and cones. We describe how tools from harmonic analysis, i.e. Fourier
analysis on groups, can be used to investigate probability density functions
(pdfs) on groups and homogeneous spaces. We consider the special case of the
Lorentz group ... | computer science |
24,069 | UnrealStereo: A Synthetic Dataset for Analyzing Stereo Vision | cs.CV | Stereo algorithm is important for robotics applications, such as quadcopter
and autonomous driving. It needs to be robust enough to handle images of
challenging conditions, such as raining or strong lighting. Textureless and
specular regions of these images make feature matching difficult and smoothness
assumption inva... | computer science |
24,070 | Super-resolution Reconstruction of SAR Image based on Non-Local Means
Denoising Combined with BP Neural Network | cs.CV | In this article, we propose a super-resolution method to resolve the problem
of image low spatial because of the limitation of imaging devices. We make use
of the strong non-linearity mapped ability of the back-propagation neural
networks(BPNN). Training sample images are got by undersampled method. The
elements chose ... | computer science |
24,071 | Registering large volume serial-section electron microscopy image sets
for neural circuit reconstruction using FFT signal whitening | cs.CV | The detailed reconstruction of neural anatomy for connectomics studies
requires a combination of resolution and large three-dimensional data capture
provided by serial section electron microscopy (ssEM). The convergence of high
throughput ssEM imaging and improved tissue preparation methods now allows ssEM
capture of c... | computer science |
24,072 | Spectral video construction from RGB video: Application to Image Guided
Neurosurgery | cs.CV | Spectral imaging has received enormous interest in the field of medical
imaging modalities. It provides a powerful tool for the analysis of different
organs and non-invasive tissues. Therefore, significant amount of research has
been conducted to explore the possibility of using spectral imaging in
biomedical applicati... | computer science |
24,073 | Fast-AT: Fast Automatic Thumbnail Generation using Deep Neural Networks | cs.CV | Fast-AT is an automatic thumbnail generation system based on deep neural
networks. It is a fully-convolutional deep neural network, which learns
specific filters for thumbnails of different sizes and aspect ratios. During
inference, the appropriate filter is selected depending on the dimensions of
the target thumbnail.... | computer science |
24,074 | The More You Know: Using Knowledge Graphs for Image Classification | cs.CV | One characteristic that sets humans apart from modern learning-based computer
vision algorithms is the ability to acquire knowledge about the world and use
that knowledge to reason about the visual world. Humans can learn about the
characteristics of objects and the relationships that occur between them to
learn a larg... | computer science |
24,075 | Temporal-Needle: A view and appearance invariant video descriptor | cs.CV | The ability to detect similar actions across videos can be very useful for
real-world applications in many fields. However, this task is still challenging
for existing systems, since videos that present the same action, can be taken
from significantly different viewing directions, performed by different actors
and back... | computer science |
24,076 | A fuzzy approach for segmentation of touching characters | cs.CV | The problem of correctly segmenting touching characters is an hard task to
solve and it is of major relevance in pattern recognition. In the recent years,
many methods and algorithms have been proposed; still, a definitive solution is
far from being found. In this paper, we propose a novel method based on fuzzy
logic. ... | computer science |
24,077 | Border-Peeling Clustering | cs.CV | In this paper, we present a novel non-parametric clustering technique, which
is based on an iterative algorithm that peels off layers of points around the
clusters. Our technique is based on the notion that each latent cluster is
comprised of layers that surround its core, where the external layers, or
border points, i... | computer science |
24,078 | Scale Coding Bag of Deep Features for Human Attribute and Action
Recognition | cs.CV | Most approaches to human attribute and action recognition in still images are
based on image representation in which multi-scale local features are pooled
across scale into a single, scale-invariant encoding. Both in bag-of-words and
the recently popular representations based on convolutional neural networks,
local fea... | computer science |
24,079 | Tinkering Under the Hood: Interactive Zero-Shot Learning with Net
Surgery | cs.CV | We consider the task of visual net surgery, in which a CNN can be
reconfigured without extra data to recognize novel concepts that may be omitted
from the training set. While most prior work make use of linguistic cues for
such "zero-shot" learning, we do so by using a pictorial language
representation of the training ... | computer science |
24,080 | Regressing Robust and Discriminative 3D Morphable Models with a very
Deep Neural Network | cs.CV | The 3D shapes of faces are well known to be discriminative. Yet despite this,
they are rarely used for face recognition and always under controlled viewing
conditions. We claim that this is a symptom of a serious but often overlooked
problem with existing methods for single view 3D face reconstruction: when
applied "in... | computer science |
24,081 | Design of Image Matched Non-Separable Wavelet using Convolutional Neural
Network | cs.CV | Image-matched nonseparable wavelets can find potential use in many
applications including image classification, segmen- tation, compressive
sensing, etc. This paper proposes a novel design methodology that utilizes
convolutional neural net- work (CNN) to design two-channel non-separable
wavelet matched to a given image... | computer science |
24,082 | Development of a Real-time Colorectal Tumor Classification System for
Narrow-band Imaging zoom-videoendoscopy | cs.CV | Colorectal endoscopy is important for the early detection and treatment of
colorectal cancer and is used worldwide. A computer-aided diagnosis (CAD)
system that provides an objective measure to endoscopists during colorectal
endoscopic examinations would be of great value. In this study, we describe a
newly developed C... | computer science |
24,083 | A Multilinear Tongue Model Derived from Speech Related MRI Data of the
Human Vocal Tract | cs.CV | We present a multilinear statistical model of the human tongue that captures
anatomical and tongue pose related shape variations separately. The model is
derived from 3D magnetic resonance imaging data of 11 speakers sustaining
speech related vocal tract configurations. The extraction is performed by using
a minimally ... | computer science |
24,084 | Objective Micro-Facial Movement Detection Using FACS-Based Regions and
Baseline Evaluation | cs.CV | Micro-facial expressions are regarded as an important human behavioural event
that can highlight emotional deception. Spotting these movements is difficult
for humans and machines, however research into using computer vision to detect
subtle facial expressions is growing in popularity. This paper proposes an
individual... | computer science |
24,085 | Reflectance Adaptive Filtering Improves Intrinsic Image Estimation | cs.CV | Separating an image into reflectance and shading layers poses a challenge for
learning approaches because no large corpus of precise and realistic ground
truth decompositions exists. The Intrinsic Images in the Wild~(IIW) dataset
provides a sparse set of relative human reflectance judgments, which serves as
a standard ... | computer science |
24,086 | SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor
Trajectories with Ground Truth | cs.CV | We introduce SceneNet RGB-D, expanding the previous work of SceneNet to
enable large scale photorealistic rendering of indoor scene trajectories. It
provides pixel-perfect ground truth for scene understanding problems such as
semantic segmentation, instance segmentation, and object detection, and also
for geometric com... | computer science |
24,087 | Visual Compiler: Synthesizing a Scene-Specific Pedestrian Detector and
Pose Estimator | cs.CV | We introduce the concept of a Visual Compiler that generates a scene specific
pedestrian detector and pose estimator without any pedestrian observations.
Given a single image and auxiliary scene information in the form of camera
parameters and geometric layout of the scene, the Visual Compiler first infers
geometricall... | computer science |
24,088 | Towards a Deep Learning Framework for Unconstrained Face Detection | cs.CV | Robust face detection is one of the most important pre-processing steps to
support facial expression analysis, facial landmarking, face recognition, pose
estimation, building of 3D facial models, etc. Although this topic has been
intensely studied for decades, it is still challenging due to numerous variants
of face im... | computer science |
24,089 | Fast, Dense Feature SDM on an iPhone | cs.CV | In this paper, we present our method for enabling dense SDM to run at over 90
FPS on a mobile device. Our contributions are two-fold. Drawing inspiration
from the FFT, we propose a Sparse Compositional Regression (SCR) framework,
which enables a significant speed up over classical dense regressors. Second,
we propose a... | computer science |
24,090 | FusionNet: A deep fully residual convolutional neural network for image
segmentation in connectomics | cs.CV | Electron microscopic connectomics is an ambitious research direction with the
goal of studying comprehensive brain connectivity maps by using
high-throughput, nano-scale microscopy. One of the main challenges in
connectomics research is developing scalable image analysis algorithms that
require minimal user interventio... | computer science |
24,091 | Medical Image Synthesis with Context-Aware Generative Adversarial
Networks | cs.CV | Computed tomography (CT) is critical for various clinical applications, e.g.,
radiotherapy treatment planning and also PET attenuation correction. However,
CT exposes radiation during acquisition, which may cause side effects to
patients. Compared to CT, magnetic resonance imaging (MRI) is much safer and
does not invol... | computer science |
24,092 | Learning Residual Images for Face Attribute Manipulation | cs.CV | Face attributes are interesting due to their detailed description of human
faces. Unlike prior researches working on attribute prediction, we address an
inverse and more challenging problem called face attribute manipulation which
aims at modifying a face image according to a given attribute value. Instead of
manipulat... | computer science |
24,093 | Output Constraint Transfer for Kernelized Correlation Filter in Tracking | cs.CV | Kernelized Correlation Filter (KCF) is one of the state-of-the-art object
trackers. However, it does not reasonably model the distribution of correlation
response during tracking process, which might cause the drifting problem,
especially when targets undergo significant appearance changes due to
occlusion, camera shak... | computer science |
24,094 | The VQA-Machine: Learning How to Use Existing Vision Algorithms to
Answer New Questions | cs.CV | One of the most intriguing features of the Visual Question Answering (VQA)
challenge is the unpredictability of the questions. Extracting the information
required to answer them demands a variety of image operations from detection
and counting, to segmentation and reconstruction. To train a method to perform
even one o... | computer science |
24,095 | Deep Residual Hashing | cs.CV | Hashing aims at generating highly compact similarity preserving code words
which are well suited for large-scale image retrieval tasks.
Most existing hashing methods first encode the images as a vector of
hand-crafted features followed by a separate binarization step to generate hash
codes. This two-stage process may... | computer science |
24,096 | Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial
Networks | cs.CV | Collecting well-annotated image datasets to train modern machine learning
algorithms is prohibitively expensive for many tasks. One appealing alternative
is rendering synthetic data where ground-truth annotations are generated
automatically. Unfortunately, models trained purely on rendered images often
fail to generali... | computer science |
24,097 | A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph
Matching | cs.CV | We study the quadratic assignment problem, in computer vision also known as
graph matching. Two leading solvers for this problem optimize the Lagrange
decomposition duals with sub-gradient and dual ascent (also known as message
passing) updates. We explore s direction further and propose several additional
Lagrangean r... | computer science |
24,098 | Video Propagation Networks | cs.CV | We propose a technique that propagates information forward through video
data. The method is conceptually simple and can be applied to tasks that
require the propagation of structured information, such as semantic labels,
based on video content. We propose a 'Video Propagation Network' that processes
video frames in an... | computer science |
24,099 | On the crucial impact of the coupling projector-backprojector in
iterative tomographic reconstruction | cs.CV | The performance of an iterative reconstruction algorithm for X-ray tomography
is strongly determined by the features of the used forward and backprojector.
For this reason, a large number of studies has focused on the to design of
projectors with increasingly higher accuracy and speed. To what extent the
accuracy of an... | computer science |
24,100 | SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan
Planes in Freehand Ultrasound | cs.CV | Identifying and interpreting fetal standard scan planes during 2D ultrasound
mid-pregnancy examinations are highly complex tasks which require years of
training. Apart from guiding the probe to the correct location, it can be
equally difficult for a non-expert to identify relevant structures within the
image. Automatic... | computer science |
24,101 | A Fusion Method Based on Decision Reliability Ratio for Finger Vein
Verification | cs.CV | Finger vein verification has developed a lot since its first proposal, but
there is still not a perfect algorithm. It is proved that algorithms with the
same overall accuracy may have different misclassified patterns. We could make
use of this complementation to fuse individual algorithms together for more
precise resu... | computer science |
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