Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
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28,602 | Adaptive Correlation Filters with Long-Term and Short-Term Memory for
Object Tracking | cs.CV | Object tracking is challenging as target objects often undergo drastic
appearance changes over time. Recently, adaptive correlation filters have been
successfully applied to object tracking. However, tracking algorithms relying
on highly adaptive correlation filters are prone to drift due to noisy updates.
Moreover, as... | computer science |
28,603 | Learning Efficient Image Representation for Person Re-Identification | cs.CV | Color names based image representation is successfully used in person
re-identification, due to the advantages of being compact, intuitively
understandable as well as being robust to photometric variance. However, there
exists the diversity between underlying distribution of color names' RGB values
and that of image pi... | computer science |
28,604 | Fast Stochastic Hierarchical Bayesian MAP for Tomographic Imaging | cs.CV | Any image recovery algorithm attempts to achieve the highest quality
reconstruction in a timely manner. The former can be achieved in several ways,
among which are by incorporating Bayesian priors that exploit natural image
tendencies to cue in on relevant phenomena. The Hierarchical Bayesian MAP
(HB-MAP) is one such a... | computer science |
28,605 | Skeleton-based Action Recognition Using LSTM and CNN | cs.CV | Recent methods based on 3D skeleton data have achieved outstanding
performance due to its conciseness, robustness, and view-independent
representation. With the development of deep learning, Convolutional Neural
Networks (CNN) and Long Short Term Memory (LSTM)-based learning methods have
achieved promising performance ... | computer science |
28,606 | Effective Approaches to Batch Parallelization for Dynamic Neural Network
Architectures | cs.CV | We present a simple dynamic batching approach applicable to a large class of
dynamic architectures that consistently yields speedups of over 10x. We provide
performance bounds when the architecture is not known a priori and a stronger
bound in the special case where the architecture is a predetermined balanced
tree. We... | computer science |
28,607 | Embedding Visual Hierarchy with Deep Networks for Large-Scale Visual
Recognition | cs.CV | In this paper, a level-wise mixture model (LMM) is developed by embedding
visual hierarchy with deep networks to support large-scale visual recognition
(i.e., recognizing thousands or even tens of thousands of object classes), and
a Bayesian approach is used to adapt a pre-trained visual hierarchy
automatically to the ... | computer science |
28,608 | Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic
Projection | cs.CV | We present a novel approach for vanishing point detection from uncalibrated
monocular images. In contrast to state-of-the-art, we make no a priori
assumptions about the observed scene. Our method is based on a convolutional
neural network (CNN) which does not use natural images, but a Gaussian sphere
representation ari... | computer science |
28,609 | Self Adversarial Training for Human Pose Estimation | cs.CV | This paper presents a deep learning based approach to the problem of human
pose estimation. We employ generative adversarial networks as our learning
paradigm in which we set up two stacked hourglass networks with the same
architecture, one as the generator and the other as the discriminator. The
generator is used as a... | computer science |
28,610 | Hyperspectral Image Restoration via Total Variation Regularized Low-rank
Tensor Decomposition | cs.CV | Hyperspectral images (HSIs) are often corrupted by a mixture of several types
of noise during the acquisition process, e.g., Gaussian noise, impulse noise,
dead lines, stripes, and many others. Such complex noise could degrade the
quality of the acquired HSIs, limiting the precision of the subsequent
processing. In thi... | computer science |
28,611 | MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis
Network | cs.CV | The inability to interpret the model prediction in semantically and visually
meaningful ways is a well-known shortcoming of most existing computer-aided
diagnosis methods. In this paper, we propose MDNet to establish a direct
multimodal mapping between medical images and diagnostic reports that can read
images, generat... | computer science |
28,612 | Visual Analytics of Movement Pattern Based on Time-Spatial Data: A
Neural Net Approach | cs.CV | Time-Spatial data plays a crucial role for different fields such as traffic
management. These data can be collected via devices such as surveillance
sensors or tracking systems. However, how to efficiently an- alyze and
visualize these data to capture essential embedded pattern information is
becoming a big challenge t... | computer science |
28,613 | Detection of bimanual gestures everywhere: why it matters, what we need
and what is missing | cs.CV | Bimanual gestures are of the utmost importance for the study of motor
coordination in humans and in everyday activities. A reliable detection of
bimanual gestures in unconstrained environments is fundamental for their
clinical study and to assess common activities of daily living. This paper
investigates techniques for... | computer science |
28,614 | Local Activity-tuned Image Filtering for Noise Removal and Image
Smoothing | cs.CV | In this paper, two local activity-tuned filtering frameworks are proposed for
noise removal and image smoothing, where the local activity measurement is
given by the clipped and normalized local variance or standard deviation. The
first framework is a modified anisotropic diffusion for noise removal of
piece-wise smoot... | computer science |
28,615 | Integration of LiDAR and Hyperspectral Data for Land-cover
Classification: A Case Study | cs.CV | In this paper, an approach is proposed to fuse LiDAR and hyperspectral data,
which considers both spectral and spatial information in a single framework.
Here, an extended self-dual attribute profile (ESDAP) is investigated to
extract spatial information from a hyperspectral data set. To extract spectral
information, a... | computer science |
28,616 | A Human and Group Behaviour Simulation Evaluation Framework utilising
Composition and Video Analysis | cs.CV | In this work we present the modular Crowd Simulation Evaluation through
Composition framework (CSEC) which provides a quantitative comparison between
different pedestrian and crowd simulation approaches. Evaluation is made based
on the comparison of source footage against synthetic video created through
novel compositi... | computer science |
28,617 | Learning in High-Dimensional Multimedia Data: The State of the Art | cs.CV | During the last decade, the deluge of multimedia data has impacted a wide
range of research areas, including multimedia retrieval, 3D tracking, database
management, data mining, machine learning, social media analysis, medical
imaging, and so on. Machine learning is largely involved in multimedia
applications of buildi... | computer science |
28,618 | Anisotropic Diffusion-based Kernel Matrix Model for Face Liveness
Detection | cs.CV | Facial recognition and verification is a widely used biometric technology in
security system. Unfortunately, face biometrics is vulnerable to spoofing
attacks using photographs or videos. In this paper, we present an anisotropic
diffusion-based kernel matrix model (ADKMM) for face liveness detection to
prevent face spo... | computer science |
28,619 | Interleaved Group Convolutions for Deep Neural Networks | cs.CV | In this paper, we present a simple and modularized neural network
architecture, named interleaved group convolutional neural networks (IGCNets).
The main point lies in a novel building block, a pair of two successive
interleaved group convolutions: primary group convolution and secondary group
convolution. The two grou... | computer science |
28,620 | Synthesis-based Robust Low Resolution Face Recognition | cs.CV | Recognition of low resolution face images is a challenging problem in many
practical face recognition systems. Methods have been proposed in the face
recognition literature for the problem which assume that the probe is low
resolution, but a high resolution gallery is available for recognition. These
attempts have been... | computer science |
28,621 | Improving speaker turn embedding by crossmodal transfer learning from
face embedding | cs.CV | Learning speaker turn embeddings has shown considerable improvement in
situations where conventional speaker modeling approaches fail. However, this
improvement is relatively limited when compared to the gain observed in face
embedding learning, which has been proven very successful for face verification
and clustering... | computer science |
28,622 | Identity Alignment by Noisy Pixel Removal | cs.CV | Identity alignment models assume precisely annotated images manually. Human
labelling is unrealistic on large sized imagery data. Detection models
introduce varying amount of noise and hamper identity alignment performance. In
this work, we propose to refine images by removing the undesired pixels. This
is achieved by ... | computer science |
28,623 | Scale-Regularized Filter Learning | cs.CV | We start out by demonstrating that an elementary learning task, corresponding
to the training of a single linear neuron in a convolutional neural network,
can be solved for feature spaces of very high dimensionality. In a second step,
acknowledging that such high-dimensional learning tasks typically benefit from
some f... | computer science |
28,624 | Adaptive Binarization for Weakly Supervised Affordance Segmentation | cs.CV | The concept of affordance is important to understand the relevance of object
parts for a certain functional interaction. Affordance types generalize across
object categories and are not mutually exclusive. This makes the segmentation
of affordance regions of objects in images a difficult task. In this work, we
build on... | computer science |
28,625 | An Analysis of Human-centered Geolocation | cs.CV | Online social networks contain a constantly increasing amount of images -
most of them focusing on people. Due to cultural and climate factors, fashion
trends and physical appearance of individuals differ from city to city. In this
paper we investigate to what extent such cues can be exploited in order to
infer the geo... | computer science |
28,626 | Enhanced Deep Residual Networks for Single Image Super-Resolution | cs.CV | Recent research on super-resolution has progressed with the development of
deep convolutional neural networks (DCNN). In particular, residual learning
techniques exhibit improved performance. In this paper, we develop an enhanced
deep super-resolution network (EDSR) with performance exceeding those of
current state-of-... | computer science |
28,627 | Wavelet-based Reflection Symmetry Detection via Textural and Color
Histograms | cs.CV | Symmetry is one of the significant visual properties inside an image plane,
to identify the geometrically balanced structures through real-world objects.
Existing symmetry detection methods rely on descriptors of the local image
features and their neighborhood behavior, resulting incomplete symmetrical axis
candidates ... | computer science |
28,628 | Checkerboard artifact free sub-pixel convolution: A note on sub-pixel
convolution, resize convolution and convolution resize | cs.CV | The most prominent problem associated with the deconvolution layer is the
presence of checkerboard artifacts in output images and dense labels. To combat
this problem, smoothness constraints, post processing and different
architecture designs have been proposed. Odena et al. highlight three sources
of checkerboard arti... | computer science |
28,629 | Foot anthropometry device and single object image thresholding | cs.CV | This paper introduces a device, algorithm and graphical user interface to
obtain anthropometric measurements of foot. Presented device facilitates
obtaining scale of image and image processing by taking one image from side
foot and underfoot simultaneously. Introduced image processing algorithm
minimizes a noise criter... | computer science |
28,630 | Rapid focus map surveying for whole slide imaging with continues sample
motion | cs.CV | Whole slide imaging (WSI) has recently been cleared for primary diagnosis in
the US. A critical challenge of WSI is to perform accurate focusing in high
speed. Traditional systems create a focus map prior to scanning. For each focus
point on the map, sample needs to be static in the x-y plane and axial scanning
is need... | computer science |
28,631 | Automatic Understanding of Image and Video Advertisements | cs.CV | There is more to images than their objective physical content: for example,
advertisements are created to persuade a viewer to take a certain action. We
propose the novel problem of automatic advertisement understanding. To enable
research on this problem, we create two datasets: an image dataset of 64,832
image ads, a... | computer science |
28,632 | Online Handwritten Mathematical Expressions Recognition System Using
Fuzzy Neural Network | cs.CV | The article describes developed information technology for online recognition
of handwritten mathematical expressions that based on proposed approaches to
handwritten symbols recognition and structural analysis. | computer science |
28,633 | Adversarial Generation of Training Examples: Applications to Moving
Vehicle License Plate Recognition | cs.CV | Generative Adversarial Networks (GAN) have attracted much research attention
recently, leading to impressive results for natural image generation. However,
to date little success was observed in using GAN generated images for improving
classification tasks. Here we attempt to explore, in the context of car license
plat... | computer science |
28,634 | Impulsive noise removal from color images with morphological filtering | cs.CV | This paper deals with impulse noise removal from color images. The proposed
noise removal algorithm employs a novel approach with morphological filtering
for color image denoising; that is, detection of corrupted pixels and removal
of the detected noise by means of morphological filtering. With the help of
computer sim... | computer science |
28,635 | Underwater object classification using scattering transform of sonar
signals | cs.CV | In this paper, we apply the scattering transform (ST), a nonlinear map based
off of a convolutional neural network (CNN), to classification of underwater
objects using sonar signals. The ST formalizes the observation that the filters
learned by a CNN have wavelet like structure. We achieve effective binary
classificati... | computer science |
28,636 | Foreground Detection in Camouflaged Scenes | cs.CV | Foreground detection has been widely studied for decades due to its
importance in many practical applications. Most of the existing methods assume
foreground and background show visually distinct characteristics and thus the
foreground can be detected once a good background model is obtained. However,
there are many si... | computer science |
28,637 | Adversarial training and dilated convolutions for brain MRI segmentation | cs.CV | Convolutional neural networks (CNNs) have been applied to various automatic
image segmentation tasks in medical image analysis, including brain MRI
segmentation. Generative adversarial networks have recently gained popularity
because of their power in generating images that are difficult to distinguish
from real images... | computer science |
28,638 | Generalised Dice overlap as a deep learning loss function for highly
unbalanced segmentations | cs.CV | Deep-learning has proved in recent years to be a powerful tool for image
analysis and is now widely used to segment both 2D and 3D medical images.
Deep-learning segmentation frameworks rely not only on the choice of network
architecture but also on the choice of loss function. When the segmentation
process targets rare... | computer science |
28,639 | A region-growing approach for automatic outcrop fracture extraction from
a three-dimensional point cloud | cs.CV | Conventional manual surveys of rock mass fractures usually require large
amounts of time and labor; yet, they provide a relatively small set of data
that cannot be considered representative of the study region. Terrestrial laser
scanners are increasingly used for fracture surveys because they can
efficiently acquire la... | computer science |
28,640 | Tensor-based approach to accelerate deformable part models | cs.CV | This article provides next step towards solving speed bottleneck of any
system that intensively uses convolutions operations (e.g. CNN). Method
described in the article is applied on deformable part models (DPM) algorithm.
Method described here is based on multidimensional tensors and provides
efficient tradeoff betwee... | computer science |
28,641 | Hierarchical Deep Recurrent Architecture for Video Understanding | cs.CV | This paper introduces the system we developed for the Youtube-8M Video
Understanding Challenge, in which a large-scale benchmark dataset was used for
multi-label video classification. The proposed framework contains hierarchical
deep architecture, including the frame-level sequence modeling part and the
video-level cla... | computer science |
28,642 | Learning the Latent "Look": Unsupervised Discovery of a Style-Coherent
Embedding from Fashion Images | cs.CV | What defines a visual style? Fashion styles emerge organically from how
people assemble outfits of clothing, making them difficult to pin down with a
computational model. Low-level visual similarity can be too specific to detect
stylistically similar images, while manually crafted style categories can be
too abstract t... | computer science |
28,643 | Individual Recognition in Schizophrenia using Deep Learning Methods with
Random Forest and Voting Classifiers: Insights from Resting State EEG Streams | cs.CV | Recently, there has been a growing interest in monitoring brain activity for
individual recognition system. So far these works are mainly focussing on
single channel data or fragment data collected by some advanced brain
monitoring modalities. In this study we propose new individual recognition
schemes based on spatio-... | computer science |
28,644 | Recovering Dense Tissue Multispectral Signal from in vivo RGB Images | cs.CV | Hyperspectral/multispectral imaging (HSI/MSI) contains rich information
clinical applications, such as 1) narrow band imaging for vascular
visualisation; 2) oxygen saturation for intraoperative perfusion monitoring and
clinical decision making [1]; 3) tissue classification and identification of
pathology [2]. The curre... | computer science |
28,645 | Place recognition: An Overview of Vision Perspective | cs.CV | Place recognition is one of the most fundamental topics in computer vision
and robotics communities, where the task is to accurately and efficiently
recognize the location of a given query image. Despite years of wisdom
accumulated in this field, place recognition still remains an open problem due
to the various ways i... | computer science |
28,646 | Creatism: A deep-learning photographer capable of creating professional
work | cs.CV | Machine-learning excels in many areas with well-defined goals. However, a
clear goal is usually not available in art forms, such as photography. The
success of a photograph is measured by its aesthetic value, a very subjective
concept. This adds to the challenge for a machine learning approach.
We introduce Creatism,... | computer science |
28,647 | Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood
Maps | cs.CV | Hyperspectral cameras can provide unique spectral signatures for consistently
distinguishing materials that can be used to solve surveillance tasks. In this
paper, we propose a novel real-time hyperspectral likelihood maps-aided
tracking method (HLT) inspired by an adaptive hyperspectral sensor. A moving
object trackin... | computer science |
28,648 | Terahertz Security Image Quality Assessment by No-reference Model
Observers | cs.CV | To provide the possibility of developing objective image quality assessment
(IQA) algorithms for THz security images, we constructed the THz security image
database (THSID) including a total of 181 THz security images with the
resolution of 127*380. The main distortion types in THz security images were
first analyzed f... | computer science |
28,649 | Machine Learning for RealisticBall Detection in RoboCup SPL | cs.CV | In this technical report, we describe the use of a machine learning approach
for detecting the realistic black and white ball currently in use in the
RoboCup Standard Platform League. Our aim is to provide a ready-to-use software
module that can be useful for the RoboCup SPL community. To this end, the
approach is inte... | computer science |
28,650 | Structured Sparse Ternary Weight Coding of Deep Neural Networks for
Efficient Hardware Implementations | cs.CV | Deep neural networks (DNNs) usually demand a large amount of operations for
real-time inference. Especially, fully-connected layers contain a large number
of weights, thus they usually need many off-chip memory accesses for inference.
We propose a weight compression method for deep neural networks, which allows
values ... | computer science |
28,651 | Deep Fisher Discriminant Learning for Mobile Hand Gesture Recognition | cs.CV | Gesture recognition is a challenging problem in the field of biometrics. In
this paper, we integrate Fisher criterion into Bidirectional Long-Short Term
Memory (BLSTM) network and Bidirectional Gated Recurrent Unit (BGRU),thus
leading to two new deep models termed as F-BLSTM and F-BGRU. BothFisher
discriminative deep m... | computer science |
28,652 | Contour and Centreline Tracking of Vessels from Angiograms using the
Classical Image Processing Techniques | cs.CV | This article deals with the problem of vessel edge and centerline detection
using classical image processing techniques due to their simpleness and
easiness to be implemented. The method is divided into four steps: the vessel
enhancement which implies a non-linear filtering proposed by Frangi, the
thresholding using Ot... | computer science |
28,653 | Pixel-variant Local Homography for Fisheye Stereo Rectification
Minimizing Resampling Distortion | cs.CV | Large field-of-view fisheye lens cameras have attracted more and more
researchers' attention in the field of robotics. However, there does not exist
a convenient off-the-shelf stereo rectification approach which can be applied
directly to fisheye stereo rig. One obvious drawback of existing methods is
that the resampli... | computer science |
28,654 | Robust Visual Tracking via Hierarchical Convolutional Features | cs.CV | Visual tracking is challenging as target objects often undergo significant
appearance changes caused by deformation, abrupt motion, background clutter and
occlusion. In this paper, we propose to exploit the rich hierarchical features
of deep convolutional neural networks to improve the accuracy and robustness of
visual... | computer science |
28,655 | Unsupervised Body Part Regression via Spatially Self-ordering
Convolutional Neural Networks | cs.CV | Automatic body part recognition for CT slices can benefit various medical
image applications. Recent deep learning methods demonstrate promising
performance, with the requirement of large amounts of labeled images for
training. The intrinsic structural or superior-inferior slice ordering
information in CT volumes is no... | computer science |
28,656 | The Surfacing of Multiview 3D Drawings via Lofting and Occlusion
Reasoning | cs.CV | The three-dimensional reconstruction of scenes from multiple views has made
impressive strides in recent years, chiefly by methods correlating isolated
feature points, intensities, or curvilinear structure. In the general setting,
i.e., without requiring controlled acquisition, limited number of objects,
abundant patte... | computer science |
28,657 | Towards End-to-end Text Spotting with Convolutional Recurrent Neural
Networks | cs.CV | In this work, we jointly address the problem of text detection and
recognition in natural scene images based on convolutional recurrent neural
networks. We propose a unified network that simultaneously localizes and
recognizes text with a single forward pass, avoiding intermediate processes
like image cropping and feat... | computer science |
28,658 | Leveraging the Path Signature for Skeleton-based Human Action
Recognition | cs.CV | Human action recognition in videos is one of the most challenging tasks in
computer vision. One important issue is how to design discriminative features
for representing spatial context and temporal dynamics. Here, we introduce a
path signature feature to encode information from intra-frame and inter-frame
contexts. A ... | computer science |
28,659 | Query-Aware Sparse Coding for Multi-Video Summarization | cs.CV | Given the explosive growth of online videos, it is becoming increasingly
important to relieve the tedious work of browsing and managing the video
content of interest. Video summarization aims at providing such a technique by
transforming one or multiple videos into a compact one. However, conventional
multi-video summa... | computer science |
28,660 | Large-scale Video Classification guided by Batch Normalized LSTM
Translator | cs.CV | Youtube-8M dataset enhances the development of large-scale video recognition
technology as ImageNet dataset has encouraged image classification, recognition
and detection of artificial intelligence fields. For this large video dataset,
it is a challenging task to classify a huge amount of multi-labels. By change
of per... | computer science |
28,661 | Discrete Multi-modal Hashing with Canonical Views for Robust Mobile
Landmark Search | cs.CV | Mobile landmark search (MLS) recently receives increasing attention for its
great practical values. However, it still remains unsolved due to two important
challenges. One is high bandwidth consumption of query transmission, and the
other is the huge visual variations of query images sent from mobile devices.
In this p... | computer science |
28,662 | Automatic Recognition of Facial Displays of Unfelt Emotions | cs.CV | Humans modify their facial expressions in order to communicate their internal
states and sometimes to mislead observers regarding their true emotional
states. Evidence in experimental psychology shows that discriminative facial
responses are short and subtle. This suggests that such behavior would be
easier to distingu... | computer science |
28,663 | UTS submission to Google YouTube-8M Challenge 2017 | cs.CV | In this paper, we present our solution to Google YouTube-8M Video
Classification Challenge 2017. We leveraged both video-level and frame-level
features in the submission. For video-level classification, we simply used a
200-mixture Mixture of Experts (MoE) layer, which achieves GAP 0.802 on the
validation set with a si... | computer science |
28,664 | Cultivating DNN Diversity for Large Scale Video Labelling | cs.CV | We investigate factors controlling DNN diversity in the context of the Google
Cloud and YouTube-8M Video Understanding Challenge. While it is well-known that
ensemble methods improve prediction performance, and that combining accurate
but diverse predictors helps, there is little knowledge on how to best promote
& meas... | computer science |
28,665 | Discriminative Optimization: Theory and Applications to Computer Vision
Problems | cs.CV | Many computer vision problems are formulated as the optimization of a cost
function. This approach faces two main challenges: (i) designing a cost
function with a local optimum at an acceptable solution, and (ii) developing an
efficient numerical method to search for one (or multiple) of these local
optima. While desig... | computer science |
28,666 | Inner-Scene Similarities as a Contextual Cue for Object Detection | cs.CV | Using image context is an effective approach for improving object detection.
Previously proposed methods used contextual cues that rely on semantic or
spatial information. In this work, we explore a different kind of contextual
information: inner-scene similarity. We present the CISS (Context by Inner
Scene Similarity)... | computer science |
28,667 | Temporal Modeling Approaches for Large-scale Youtube-8M Video
Understanding | cs.CV | This paper describes our solution for the video recognition task of the
Google Cloud and YouTube-8M Video Understanding Challenge that ranked the 3rd
place. Because the challenge provides pre-extracted visual and audio features
instead of the raw videos, we mainly investigate various temporal modeling
approaches to agg... | computer science |
28,668 | Knowledge-Guided Recurrent Neural Network Learning for Task-Oriented
Action Prediction | cs.CV | This paper aims at task-oriented action prediction, i.e., predicting a
sequence of actions towards accomplishing a specific task under a certain
scene, which is a new problem in computer vision research. The main challenges
lie in how to model task-specific knowledge and integrate it in the learning
procedure. In this ... | computer science |
28,669 | Rethinking Reprojection: Closing the Loop for Pose-aware
ShapeReconstruction from a Single Image | cs.CV | An emerging problem in computer vision is the reconstruction of 3D shape and
pose of an object from a single image. Hitherto, the problem has been addressed
through the application of canonical deep learning methods to regress from the
image directly to the 3D shape and pose labels. These approaches, however, are
probl... | computer science |
28,670 | Binarized Convolutional Neural Networks with Separable Filters for
Efficient Hardware Acceleration | cs.CV | State-of-the-art convolutional neural networks are enormously costly in both
compute and memory, demanding massively parallel GPUs for execution. Such
networks strain the computational capabilities and energy available to embedded
and mobile processing platforms, restricting their use in many important
applications. In... | computer science |
28,671 | Original Loop-closure Detection Algorithm for Monocular vSLAM | cs.CV | Vision-based simultaneous localization and mapping (vSLAM) is a
well-established problem in mobile robotics and monocular vSLAM is one of the
most challenging variations of that problem nowadays. In this work we study one
of the core post-processing optimization mechanisms in vSLAM, e.g. loop-closure
detection. We anal... | computer science |
28,672 | Modified Alpha-Rooting Color Image Enhancement Method On The Two-Side
2-D Quaternion Discrete Fourier Transform And The 2-D Discrete Fourier
Transform | cs.CV | Color in an image is resolved into 3 or 4 color components and 2-Dimages of
these components are stored in separate channels. Most of the color image
enhancement algorithms are applied channel-by-channel on each image. But such a
system of color image processing is not processing the original color. When a
color image ... | computer science |
28,673 | RED: Reinforced Encoder-Decoder Networks for Action Anticipation | cs.CV | Action anticipation aims to detect an action before it happens. Many real
world applications in robotics and surveillance are related to this predictive
capability. Current methods address this problem by first anticipating visual
representations of future frames and then categorizing the anticipated
representations to... | computer science |
28,674 | Generative Adversarial Network based on Resnet for Conditional Image
Restoration | cs.CV | The GANs promote an adversarive game to approximate complex and jointed
example probability. The networks driven by noise generate fake examples to
approximate realistic data distributions. Later the conditional GAN merges
prior-conditions as input in order to transfer attribute vectors to the
corresponding data. Howev... | computer science |
28,675 | Chinese Typography Transfer | cs.CV | In this paper, we propose a new network architecture for Chinese typography
transformation based on deep learning. The architecture consists of two
sub-networks: (1)a fully convolutional network(FCN) aiming at transferring
specified typography style to another in condition of preserving structure
information; (2)an adv... | computer science |
28,676 | Expected exponential loss for gaze-based video and volume ground truth
annotation | cs.CV | Many recent machine learning approaches used in medical imaging are highly
reliant on large amounts of image and ground truth data. In the context of
object segmentation, pixel-wise annotations are extremely expensive to collect,
especially in video and 3D volumes. To reduce this annotation burden, we
propose a novel f... | computer science |
28,677 | Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent
Neural Contextual Learning and Direct Loss Function | cs.CV | Deep neural networks have demonstrated very promising performance on accurate
segmentation of challenging organs (e.g., pancreas) in abdominal CT and MRI
scans. The current deep learning approaches conduct pancreas segmentation by
processing sequences of 2D image slices independently through deep, dense
per-pixel maski... | computer science |
28,678 | Pathological OCT Retinal Layer Segmentation using Branch Residual
U-shape Networks | cs.CV | The automatic segmentation of retinal layer structures enables
clinically-relevant quantification and monitoring of eye disorders over time in
OCT imaging. Eyes with late-stage diseases are particularly challenging to
segment, as their shape is highly warped due to pathological biomarkers. In
this context, we propose a... | computer science |
28,679 | Query-Focused Video Summarization: Dataset, Evaluation, and A Memory
Network Based Approach | cs.CV | Recent years have witnessed a resurgence of interest in video summarization.
However, one of the main obstacles to the research on video summarization is
the user subjectivity - users have various preferences over the summaries. The
subjectiveness causes at least two problems. First, no single video summarizer
fits all... | computer science |
28,680 | Non-Linear Subspace Clustering with Learned Low-Rank Kernels | cs.CV | In this paper, we present a kernel subspace clustering method that can handle
non-linear models. In contrast to recent kernel subspace clustering methods
which use predefined kernels, we propose to learn a low-rank kernel matrix,
with which mapped data in feature space are not only low-rank but also
self-expressive. In... | computer science |
28,681 | Tracking as Online Decision-Making: Learning a Policy from Streaming
Videos with Reinforcement Learning | cs.CV | We formulate tracking as an online decision-making process, where a tracking
agent must follow an object despite ambiguous image frames and a limited
computational budget. Crucially, the agent must decide where to look in the
upcoming frames, when to reinitialize because it believes the target has been
lost, and when t... | computer science |
28,682 | MoCoGAN: Decomposing Motion and Content for Video Generation | cs.CV | Visual signals in a video can be divided into content and motion. While
content specifies which objects are in the video, motion describes their
dynamics. Based on this prior, we propose the Motion and Content decomposed
Generative Adversarial Network (MoCoGAN) framework for video generation. The
proposed framework gen... | computer science |
28,683 | "Maximizing rigidity" revisited: a convex programming approach for
generic 3D shape reconstruction from multiple perspective views | cs.CV | Rigid structure-from-motion (RSfM) and non-rigid structure-from-motion
(NRSfM) have long been treated in the literature as separate (different)
problems. Inspired by a previous work which solved directly for 3D scene
structure by factoring the relative camera poses out, we revisit the principle
of "maximizing rigidity"... | computer science |
28,684 | Residual Features and Unified Prediction Network for Single Stage
Detection | cs.CV | Recently, a lot of single stage detectors using multi-scale features have
been actively proposed. They are much faster than two stage detectors that use
region proposal networks (RPN) without much degradation in the detection
performances. However, the feature maps in the lower layers close to the input
which are respo... | computer science |
28,685 | Designing Effective Inter-Pixel Information Flow for Natural Image
Matting | cs.CV | We present a novel, purely affinity-based natural image matting algorithm.
Our method relies on carefully defined pixel-to-pixel connections that enable
effective use of information available in the image. We control the information
flow from the known-opacity regions into the unknown region, as well as within
the unkn... | computer science |
28,686 | Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy | cs.CV | Augmenting X-ray imaging with 3D roadmap to improve guidance is a common
strategy. Such approaches benefit from automated analysis of the X-ray images,
such as the automatic detection and tracking of instruments. In this paper, we
propose a real-time method to segment the catheter and guidewire in 2D X-ray
fluoroscopic... | computer science |
28,687 | Aesthetic-Driven Image Enhancement by Adversarial Learning | cs.CV | We introduce EnhanceGAN, an adversarial learning based model that performs
automatic image enhancement. Traditional image enhancement frameworks involve
training separate models for automatic cropping or color enhancement in a
fully-supervised manner, which requires expensive annotations in the form of
image pairs. In ... | computer science |
28,688 | Dominant Sets for "Constrained" Image Segmentation | cs.CV | Image segmentation has come a long way since the early days of computer
vision, and still remains a challenging task. Modern variations of the
classical (purely bottom-up) approach, involve, e.g., some form of user
assistance (interactive segmentation) or ask for the simultaneous segmentation
of two or more images (co-... | computer science |
28,689 | Show and Recall: Learning What Makes Videos Memorable | cs.CV | With the explosion of video content on the Internet, there is a need for
research on methods for video analysis which take human cognition into account.
One such cognitive measure is memorability, or the ability to recall visual
content after watching it. Prior research has looked into image memorability
and shown that... | computer science |
28,690 | Make Your Bone Great Again : A study on Osteoporosis Classification | cs.CV | Osteoporosis can be identified by looking at 2D x-ray images of the bone. The
high degree of similarity between images of a healthy bone and a diseased one
makes classification a challenge. A good bone texture characterization
technique is essential for identifying osteoporosis cases. Standard texture
feature extractio... | computer science |
28,691 | Benchmarking and Error Diagnosis in Multi-Instance Pose Estimation | cs.CV | We propose a new method to analyze the impact of errors in algorithms for
multi-instance pose estimation and a principled benchmark that can be used to
compare them. We define and characterize three classes of errors -
localization, scoring, and background - study how they are influenced by
instance attributes and thei... | computer science |
28,692 | Incremental Boosting Convolutional Neural Network for Facial Action Unit
Recognition | cs.CV | Recognizing facial action units (AUs) from spontaneous facial expressions is
still a challenging problem. Most recently, CNNs have shown promise on facial
AU recognition. However, the learned CNNs are often overfitted and do not
generalize well to unseen subjects due to limited AU-coded training images. We
proposed a n... | computer science |
28,693 | Slanted Stixels: Representing San Francisco's Steepest Streets | cs.CV | In this work we present a novel compact scene representation based on Stixels
that infers geometric and semantic information. Our approach overcomes the
previous rather restrictive geometric assumptions for Stixels by introducing a
novel depth model to account for non-flat roads and slanted objects. Both
semantic and d... | computer science |
28,694 | Wide Inference Network for Image Denoising via Learning
Pixel-distribution Prior | cs.CV | We explore an innovative strategy for image denoising by using convolutional
neural networks (CNN) to learn similar pixel-distribution features from noisy
images. Many types of image noise follow a certain pixel-distribution in
common, such as additive white Gaussian noise (AWGN). By increasing CNN's width
with larger ... | computer science |
28,695 | Fast and Accurate Image Super Resolution by Deep CNN with Skip
Connection and Network in Network | cs.CV | We propose a highly efficient and faster Single Image Super-Resolution (SISR)
model with Deep Convolutional neural networks (Deep CNN). Deep CNN have
recently shown that they have a significant reconstruction performance on
single-image super-resolution. Current trend is using deeper CNN layers to
improve performance. ... | computer science |
28,696 | Visually Aligned Word Embeddings for Improving Zero-shot Learning | cs.CV | Zero-shot learning (ZSL) highly depends on a good semantic embedding to
connect the seen and unseen classes. Recently, distributed word embeddings
(DWE) pre-trained from large text corpus have become a popular choice to draw
such a connection. Compared with human defined attributes, DWEs are more
scalable and easier to... | computer science |
28,697 | Discriminative Transformation Learning for Fuzzy Sparse Subspace
Clustering | cs.CV | This paper develops a novel iterative framework for subspace clustering in a
learned discriminative feature domain. This framework consists of two modules
of fuzzy sparse subspace clustering and discriminative transformation learning.
In the first module, fuzzy latent labels containing discriminative information
and la... | computer science |
28,698 | Pruning Convolutional Neural Networks for Image Instance Retrieval | cs.CV | In this work, we focus on the problem of image instance retrieval with deep
descriptors extracted from pruned Convolutional Neural Networks (CNN). The
objective is to heavily prune convolutional edges while maintaining retrieval
performance. To this end, we introduce both data-independent and data-dependent
heuristics ... | computer science |
28,699 | DCTM: Discrete-Continuous Transformation Matching for Semantic Flow | cs.CV | Techniques for dense semantic correspondence have provided limited ability to
deal with the geometric variations that commonly exist between semantically
similar images. While variations due to scale and rotation have been examined,
there lack practical solutions for more complex deformations such as affine
transformat... | computer science |
28,700 | APE-GAN: Adversarial Perturbation Elimination with GAN | cs.CV | Although neural networks could achieve state-of-the-art performance while
recongnizing images, they often suffer a tremendous defeat from adversarial
examples--inputs generated by utilizing imperceptible but intentional
perturbation to clean samples from the datasets. How to defense against
adversarial examples is an i... | computer science |
28,701 | Order-Free RNN with Visual Attention for Multi-Label Classification | cs.CV | In this paper, we propose the joint learning attention and recurrent neural
network (RNN) models for multi-label classification. While approaches based on
the use of either model exist (e.g., for the task of image captioning),
training such existing network architectures typically require pre-defined
label sequences. F... | computer science |
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