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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26,302 | Deep learning based fence segmentation and removal from an image using a
video sequence | cs.CV | Conventional approaches to image de-fencing use multiple adjacent frames for
segmentation of fences in the reference image and are limited to restoring
images of static scenes only. In this paper, we propose a de-fencing algorithm
for images of dynamic scenes using an occlusion-aware optical flow method. We
divide the ... | computer science |
26,303 | Deep Joint Rain Detection and Removal from a Single Image | cs.CV | In this paper, we address a rain removal problem from a single image, even in
the presence of heavy rain and rain streak accumulation. Our core ideas lie in
the new rain image models and a novel deep learning architecture. We first
modify an existing model comprising a rain streak layer and a background layer,
by addin... | computer science |
26,304 | Visual Fashion-Product Search at SK Planet | cs.CV | We build a large-scale visual search system which finds similar product
images given a fashion item. Defining similarity among arbitrary
fashion-products is still remains a challenging problem, even there is no exact
ground-truth. To resolve this problem, we define more than 90 fashion-related
attributes, and combinati... | computer science |
26,305 | Linear Support Tensor Machine: Pedestrian Detection in Thermal Infrared
Images | cs.CV | Pedestrian detection in thermal infrared images poses unique challenges
because of the low resolution and noisy nature of the image. Here we propose a
mid-level attribute in the form of multidimensional template, or tensor, using
Local Steering Kernel (LSK) as low-level descriptors for detecting pedestrians
in far infr... | computer science |
26,306 | Optimistic and Pessimistic Neural Networks for Scene and Object
Recognition | cs.CV | In this paper the application of uncertainty modeling to convolutional neural
networks is evaluated. A novel method for adjusting the network's predictions
based on uncertainty information is introduced. This allows the network to be
either optimistic or pessimistic in its prediction scores. The proposed method
builds ... | computer science |
26,307 | Super-resolving multiresolution images with band-independant geometry of
multispectral pixels | cs.CV | A new resolution enhancement method is presented for multispectral and
multi-resolution images, such as these provided by the Sentinel-2 satellites.
Starting from the highest resolution bands, band-dependent information
(reflectance) is separated from information that is common to all bands
(geometry of scene elements)... | computer science |
26,308 | BioLeaf: a professional mobile application to measure foliar damage
caused by insect herbivory | cs.CV | Soybean is one of the ten greatest crops in the world, answering for
billion-dollar businesses every year. This crop suffers from insect herbivory
that costs millions from producers. Hence, constant monitoring of the crop
foliar damage is necessary to guide the application of insecticides. However,
current methods to m... | computer science |
26,309 | Robust Regression For Image Binarization Under Heavy Noises and
Nonuniform Background | cs.CV | This paper presents a robust regression approach for image binarization under
significant background variations and observation noises. The work is motivated
by the need of identifying foreground regions in noisy microscopic image or
degraded document images, where significant background variation and severe
noise make... | computer science |
26,310 | Swipe Mosaics from Video | cs.CV | A panoramic image mosaic is an attractive visualization for viewing many
overlapping photos, but its images must be both captured and processed
correctly to produce an acceptable composite. We propose Swipe Mosaics, an
interactive visualization that places the individual video frames on a 2D
planar map that represents ... | computer science |
26,311 | Learning Language-Visual Embedding for Movie Understanding with
Natural-Language | cs.CV | Learning a joint language-visual embedding has a number of very appealing
properties and can result in variety of practical application, including
natural language image/video annotation and search. In this work, we study
three different joint language-visual neural network model architectures. We
evaluate our models o... | computer science |
26,312 | De-noising, Stabilizing and Completing 3D Reconstructions On-the-go
using Plane Priors | cs.CV | Creating 3D maps on robots and other mobile devices has become a reality in
recent years. Online 3D reconstruction enables many exciting applications in
robotics and AR/VR gaming. However, the reconstructions are noisy and generally
incomplete. Moreover, during onine reconstruction, the surface changes with
every newly... | computer science |
26,313 | Image Retrieval with Fisher Vectors of Binary Features | cs.CV | Recently, the Fisher vector representation of local features has attracted
much attention because of its effectiveness in both image classification and
image retrieval. Another trend in the area of image retrieval is the use of
binary features such as ORB, FREAK, and BRISK. Considering the significant
performance impro... | computer science |
26,314 | Automated Breast Lesion Segmentation in Ultrasound Images | cs.CV | The main objective of this project is to segment different breast ultrasound
images to find out lesion area by discarding the low contrast regions as well
as the inherent speckle noise. The proposed method consists of three stages
(removing noise, segmentation, classification) in order to extract the correct
lesion. We... | computer science |
26,315 | Tensor Based Second Order Variational Model for Image Reconstruction | cs.CV | Second order total variation (SOTV) models have advantages for image
reconstruction over their first order counterparts including their ability to
remove the staircase artefact in the reconstructed image, but they tend to blur
the reconstructed image. To overcome this drawback, we introduce a new Tensor
Weighted Second... | computer science |
26,316 | Semi Automatic Color Segmentation of Document Pages | cs.CV | -This paper presents a semi automatic method used to segment color documents
into different uniform color plans. The practical application is dedicated to
administrative documents segmentation. In these documents, like in many other
cases, color has a semantic meaning: it is then possible to identify some
specific regi... | computer science |
26,317 | House price estimation from visual and textual features | cs.CV | Most existing automatic house price estimation systems rely only on some
textual data like its neighborhood area and the number of rooms. The final
price is estimated by a human agent who visits the house and assesses it
visually. In this paper, we propose extracting visual features from house
photographs and combining... | computer science |
26,318 | Learning convolutional neural network to maximize Pos@Top performance
measure | cs.CV | In the machine learning problems, the performance measure is used to evaluate
the machine learning models. Recently, the number positive data points ranked
at the top positions (Pos@Top) has been a popular performance measure in the
machine learning community. In this paper, we propose to learn a convolutional
neural n... | computer science |
26,319 | Non-flat Road Detection Based on A Local Descriptor | cs.CV | The detection of road and free space remains challenging for non-flat plane,
especially with the varying latitudinal and longitudinal slope or in the case
of multi-ground plane. In this paper, we propose a framework of the ground
plane detection with stereo vision. The main contribution of this paper is a
newly propose... | computer science |
26,320 | Blind Facial Image Quality Enhancement using Non-Rigid Semantic Patches | cs.CV | We propose to combine semantic data and registration algorithms to solve
various image processing problems such as denoising, super-resolution and
color-correction. It is shown how such new techniques can achieve significant
quality enhancement, both visually and quantitatively, in the case of facial
image enhancement.... | computer science |
26,321 | Task Specific Adversarial Cost Function | cs.CV | The cost function used to train a generative model should fit the purpose of
the model. If the model is intended for tasks such as generating perceptually
correct samples, it is beneficial to maximise the likelihood of a sample drawn
from the model, Q, coming from the same distribution as the training data, P.
This is ... | computer science |
26,322 | A Transportation $L^p$ Distance for Signal Analysis | cs.CV | Transport based distances, such as the Wasserstein distance and earth mover's
distance, have been shown to be an effective tool in signal and image analysis.
The success of transport based distances is in part due to their Lagrangian
nature which allows it to capture the important variations in many signal
classes. How... | computer science |
26,323 | YouTube-8M: A Large-Scale Video Classification Benchmark | cs.CV | Many recent advancements in Computer Vision are attributed to large datasets.
Open-source software packages for Machine Learning and inexpensive commodity
hardware have reduced the barrier of entry for exploring novel approaches at
scale. It is possible to train models over millions of examples within a few
days. Altho... | computer science |
26,324 | Scalable Discrete Supervised Hash Learning with Asymmetric Matrix
Factorization | cs.CV | Hashing method maps similar data to binary hashcodes with smaller hamming
distance, and it has received a broad attention due to its low storage cost and
fast retrieval speed. However, the existing limitations make the present
algorithms difficult to deal with large-scale datasets: (1) discrete
constraints are involved... | computer science |
26,325 | Video Summarization using Deep Semantic Features | cs.CV | This paper presents a video summarization technique for an Internet video to
provide a quick way to overview its content. This is a challenging problem
because finding important or informative parts of the original video requires
to understand its content. Furthermore the content of Internet videos is very
diverse, ran... | computer science |
26,326 | Understanding data augmentation for classification: when to warp? | cs.CV | In this paper we investigate the benefit of augmenting data with
synthetically created samples when training a machine learning classifier. Two
approaches for creating additional training samples are data warping, which
generates additional samples through transformations applied in the data-space,
and synthetic over-s... | computer science |
26,327 | Towards the effectiveness of Deep Convolutional Neural Network based
Fast Random Forest Classifier | cs.CV | Deep Learning is considered to be a quite young in the area of machine
learning research, found its effectiveness in dealing complex yet high
dimensional dataset that includes but limited to images, text and speech etc.
with multiple levels of representation and abstraction. As there are a plethora
of research on these... | computer science |
26,328 | Graph Based Convolutional Neural Network | cs.CV | The benefit of localized features within the regular domain has given rise to
the use of Convolutional Neural Networks (CNNs) in machine learning, with great
proficiency in the image classification. The use of CNNs becomes problematic
within the irregular spatial domain due to design and convolution of a kernel
filter ... | computer science |
26,329 | Deep Architectures for Face Attributes | cs.CV | We train a deep convolutional neural network to perform identity
classification using a new dataset of public figures annotated with age,
gender, ethnicity and emotion labels, and then fine-tune it for attribute
classification. An optimal sharing pattern of computational resources within
this network is determined by e... | computer science |
26,330 | A Simple, Fast and Highly-Accurate Algorithm to Recover 3D Shape from 2D
Landmarks on a Single Image | cs.CV | Three-dimensional shape reconstruction of 2D landmark points on a single
image is a hallmark of human vision, but is a task that has been proven
difficult for computer vision algorithms. We define a feed-forward deep neural
network algorithm that can reconstruct 3D shapes from 2D landmark points almost
perfectly (i.e.,... | computer science |
26,331 | CNN-aware Binary Map for General Semantic Segmentation | cs.CV | In this paper we introduce a novel method for general semantic segmentation
that can benefit from general semantics of Convolutional Neural Network (CNN).
Our segmentation proposes visually and semantically coherent image segments. We
use binary encoding of CNN features to overcome the difficulty of the
clustering on t... | computer science |
26,332 | A comparative study of complexity of handwritten Bharati characters with
that of major Indian scripts | cs.CV | We present Bharati, a simple, novel script that can represent the characters
of a majority of contemporary Indian scripts. The shapes/motifs of Bharati
characters are drawn from some of the simplest characters of existing Indian
scripts. Bharati characters are designed such that they strictly reflect the
underlying pho... | computer science |
26,333 | Modelling depth for nonparametric foreground segmentation using RGBD
devices | cs.CV | The problem of detecting changes in a scene and segmenting the foreground
from background is still challenging, despite previous work. Moreover, new RGBD
capturing devices include depth cues, which could be incorporated to improve
foreground segmentation. In this work, we present a new nonparametric approach
where a un... | computer science |
26,334 | Kernel Methods on Approximate Infinite-Dimensional Covariance Operators
for Image Classification | cs.CV | This paper presents a novel framework for visual object recognition using
infinite-dimensional covariance operators of input features in the paradigm of
kernel methods on infinite-dimensional Riemannian manifolds. Our formulation
provides in particular a rich representation of image features by exploiting
their non-lin... | computer science |
26,335 | Pano2CAD: Room Layout From A Single Panorama Image | cs.CV | This paper presents a method of estimating the geometry of a room and the 3D
pose of objects from a single 360-degree panorama image. Assuming Manhattan
World geometry, we formulate the task as a Bayesian inference problem in which
we estimate positions and orientations of walls and objects. The method
combines surface... | computer science |
26,336 | Redefining Binarization and the Visual Archetype | cs.CV | Although binarization is considered passe, it still remains a highly popular
research topic. In this paper we propose a rethinking of what binarization is.
We introduce the notion of the visual archetype as the ideal form of any one
document. Binarization can be defined as the restoration of the visual
archetype for a ... | computer science |
26,337 | Two-stage Convolutional Part Heatmap Regression for the 1st 3D Face
Alignment in the Wild (3DFAW) Challenge | cs.CV | This paper describes our submission to the 1st 3D Face Alignment in the Wild
(3DFAW) Challenge. Our method builds upon the idea of convolutional part
heatmap regression [1], extending it for 3D face alignment. Our method
decomposes the problem into two parts: (a) X,Y (2D) estimation and (b) Z
(depth) estimation. At the... | computer science |
26,338 | A CNN Cascade for Landmark Guided Semantic Part Segmentation | cs.CV | This paper proposes a CNN cascade for semantic part segmentation guided by
pose-specific information encoded in terms of a set of landmarks (or
keypoints). There is large amount of prior work on each of these tasks
separately, yet, to the best of our knowledge, this is the first time in
literature that the interplay be... | computer science |
26,339 | Training a Feedback Loop for Hand Pose Estimation | cs.CV | We propose an entirely data-driven approach to estimating the 3D pose of a
hand given a depth image. We show that we can correct the mistakes made by a
Convolutional Neural Network trained to predict an estimate of the 3D pose by
using a feedback loop. The components of this feedback loop are also Deep
Networks, optimi... | computer science |
26,340 | A deep representation for depth images from synthetic data | cs.CV | Convolutional Neural Networks (CNNs) trained on large scale RGB databases
have become the secret sauce in the majority of recent approaches for object
categorization from RGB-D data. Thanks to colorization techniques, these
methods exploit the filters learned from 2D images to extract meaningful
representations in 2.5D... | computer science |
26,341 | Latent fingerprint minutia extraction using fully convolutional network | cs.CV | Minutiae play a major role in fingerprint identification. Extracting reliable
minutiae is difficult for latent fingerprints which are usually of poor
quality. As the limitation of traditional handcrafted features, a fully
convolutional network (FCN) is utilized to learn features directly from data to
overcome complex b... | computer science |
26,342 | Microscopic Pedestrian Flow Characteristics: Development of an Image
Processing Data Collection and Simulation Model | cs.CV | Microscopic pedestrian studies consider detailed interaction of pedestrians
to control their movement in pedestrian traffic flow. The tools to collect the
microscopic data and to analyze microscopic pedestrian flow are still very much
in its infancy. The microscopic pedestrian flow characteristics need to be
understood... | computer science |
26,343 | How Transferable are CNN-based Features for Age and Gender
Classification? | cs.CV | Age and gender are complementary soft biometric traits for face recognition.
Successful estimation of age and gender from facial images taken under
real-world conditions can contribute improving the identification results in
the wild. In this study, in order to achieve robust age and gender
classification in the wild, ... | computer science |
26,344 | Near-Infrared Image Dehazing Via Color Regularization | cs.CV | Near-infrared imaging can capture haze-free near-infrared gray images and
visible color images, according to physical scattering models, e.g., Rayleigh
or Mie models. However, there exist serious discrepancies in brightness and
image structures between the near-infrared gray images and the visible color
images. The dir... | computer science |
26,345 | Deep Feature Consistent Variational Autoencoder | cs.CV | We present a novel method for constructing Variational Autoencoder (VAE).
Instead of using pixel-by-pixel loss, we enforce deep feature consistency
between the input and the output of a VAE, which ensures the VAE's output to
preserve the spatial correlation characteristics of the input, thus leading the
output to have ... | computer science |
26,346 | Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal
Event Detection | cs.CV | Most of the crowd abnormal event detection methods rely on complex
hand-crafted features to represent the crowd motion and appearance.
Convolutional Neural Networks (CNN) have shown to be a powerful tool with
excellent representational capacities, which can leverage the need for
hand-crafted features. In this paper, we... | computer science |
26,347 | MinMax Radon Barcodes for Medical Image Retrieval | cs.CV | Content-based medical image retrieval can support diagnostic decisions by
clinical experts. Examining similar images may provide clues to the expert to
remove uncertainties in his/her final diagnosis. Beyond conventional feature
descriptors, binary features in different ways have been recently proposed to
encode the im... | computer science |
26,348 | Stacked Autoencoders for Medical Image Search | cs.CV | Medical images can be a valuable resource for reliable information to support
medical diagnosis. However, the large volume of medical images makes it
challenging to retrieve relevant information given a particular scenario. To
solve this challenge, content-based image retrieval (CBIR) attempts to
characterize images (o... | computer science |
26,349 | Near-Infrared Coloring via a Contrast-Preserving Mapping Model | cs.CV | Near-infrared gray images captured together with corresponding visible color
images have recently proven useful for image restoration and classification.
This paper introduces a new coloring method to add colors to near-infrared gray
images based on a contrast-preserving mapping model. A naive coloring method
directly ... | computer science |
26,350 | Rain Removal via Shrinkage-Based Sparse Coding and Learned Rain
Dictionary | cs.CV | This paper introduces a new rain removal model based on the shrinkage of the
sparse codes for a single image. Recently, dictionary learning and sparse
coding have been widely used for image restoration problems. These methods can
also be applied to the rain removal by learning two types of rain and non-rain
dictionarie... | computer science |
26,351 | Seeing into Darkness: Scotopic Visual Recognition | cs.CV | Images are formed by counting how many photons traveling from a given set of
directions hit an image sensor during a given time interval. When photons are
few and far in between, the concept of `image' breaks down and it is best to
consider directly the flow of photons. Computer vision in this regime, which we
call `sc... | computer science |
26,352 | Rain structure transfer using an exemplar rain image for synthetic rain
image generation | cs.CV | This letter proposes a simple method of transferring rain structures of a
given exemplar rain image into a target image. Given the exemplar rain image
and its corresponding masked rain image, rain patches including rain structures
are extracted randomly, and then residual rain patches are obtained by
subtracting those ... | computer science |
26,353 | Can Ground Truth Label Propagation from Video help Semantic
Segmentation? | cs.CV | For state-of-the-art semantic segmentation task, training convolutional
neural networks (CNNs) requires dense pixelwise ground truth (GT) labeling,
which is expensive and involves extensive human effort. In this work, we study
the possibility of using auxiliary ground truth, so-called \textit{pseudo
ground truth} (PGT)... | computer science |
26,354 | Prediction of Manipulation Actions | cs.CV | Looking at a person's hands one often can tell what the person is going to do
next, how his/her hands are moving and where they will be, because an actor's
intentions shape his/her movement kinematics during action execution.
Similarly, active systems with real-time constraints must not simply rely on
passive video-seg... | computer science |
26,355 | Real Time Fine-Grained Categorization with Accuracy and Interpretability | cs.CV | A well-designed fine-grained categorization system usually has three
contradictory requirements: accuracy (the ability to identify objects among
subordinate categories); interpretability (the ability to provide
human-understandable explanation of recognition system behavior); and
efficiency (the speed of the system). T... | computer science |
26,356 | Image Aesthetic Assessment: An Experimental Survey | cs.CV | This survey aims at reviewing recent computer vision techniques used in the
assessment of image aesthetic quality. Image aesthetic assessment aims at
computationally distinguishing high-quality photos from low-quality ones based
on photographic rules, typically in the form of binary classification or
quality scoring. A... | computer science |
26,357 | Adaptive Graph-based Total Variation for Tomographic Reconstructions | cs.CV | Sparsity exploiting image reconstruction (SER) methods have been extensively
used with Total Variation (TV) regularization for tomographic reconstructions.
Local TV methods fail to preserve texture details and often create additional
artefacts due to over-smoothing. Non-Local TV (NLTV) methods have been proposed
as a s... | computer science |
26,358 | A novel and effective scoring scheme for structure classification and
pairwise similarity measurement | cs.CV | Protein tertiary structure defines its functions, classification and binding
sites. Similar structural characteristics between two proteins often lead to
the similar characteristics thereof. Determining structural similarity
accurately in real time is a crucial research issue. In this paper, we present
a novel and effe... | computer science |
26,359 | Sparsity-based Color Image Super Resolution via Exploiting Cross Channel
Constraints | cs.CV | Sparsity constrained single image super-resolution (SR) has been of much
recent interest. A typical approach involves sparsely representing patches in a
low-resolution (LR) input image via a dictionary of example LR patches, and
then using the coefficients of this representation to generate the
high-resolution (HR) out... | computer science |
26,360 | Fast Image Classification by Boosting Fuzzy Classifiers | cs.CV | This paper presents a novel approach to visual objects classification based
on generating simple fuzzy classifiers using local image features to
distinguish between one known class and other classes. Boosting meta learning
is used to find the most representative local features. The proposed approach
is tested on a stat... | computer science |
26,361 | Knowledge Guided Disambiguation for Large-Scale Scene Classification
with Multi-Resolution CNNs | cs.CV | Convolutional Neural Networks (CNNs) have made remarkable progress on scene
recognition, partially due to these recent large-scale scene datasets, such as
the Places and Places2. Scene categories are often defined by multi-level
information, including local objects, global layout, and background
environment, thus leadi... | computer science |
26,362 | Feature Learning from Spectrograms for Assessment of Personality Traits | cs.CV | Several methods have recently been proposed to analyze speech and
automatically infer the personality of the speaker. These methods often rely on
prosodic and other hand crafted speech processing features extracted with
off-the-shelf toolboxes. To achieve high accuracy, numerous features are
typically extracted using c... | computer science |
26,363 | Recognizing and Presenting the Storytelling Video Structure with Deep
Multimodal Networks | cs.CV | This paper presents a novel approach for temporal and semantic segmentation
of edited videos into meaningful segments, from the point of view of the
storytelling structure. The objective is to decompose a long video into more
manageable sequences, which can in turn be used to retrieve the most
significant parts of it g... | computer science |
26,364 | Learning Optimal Parameters for Multi-target Tracking with Contextual
Interactions | cs.CV | We describe an end-to-end framework for learning parameters of min-cost flow
multi-target tracking problem with quadratic trajectory interactions including
suppression of overlapping tracks and contextual cues about cooccurrence of
different objects. Our approach utilizes structured prediction with a
tracking-specific ... | computer science |
26,365 | Exploiting Depth from Single Monocular Images for Object Detection and
Semantic Segmentation | cs.CV | Augmenting RGB data with measured depth has been shown to improve the
performance of a range of tasks in computer vision including object detection
and semantic segmentation. Although depth sensors such as the Microsoft Kinect
have facilitated easy acquisition of such depth information, the vast majority
of images used... | computer science |
26,366 | A Deep Spatial Contextual Long-term Recurrent Convolutional Network for
Saliency Detection | cs.CV | Traditional saliency models usually adopt hand-crafted image features and
human-designed mechanisms to calculate local or global contrast. In this paper,
we propose a novel computational saliency model, i.e., deep spatial contextual
long-term recurrent convolutional network (DSCLRCN) to predict where people
looks in na... | computer science |
26,367 | Searching Scenes by Abstracting Things | cs.CV | In this paper we propose to represent a scene as an abstraction of 'things'.
We start from 'things' as generated by modern object proposals, and we
investigate their immediately observable properties: position, size, aspect
ratio and color, and those only. Where the recent successes and excitement of
the field lie in o... | computer science |
26,368 | Do They All Look the Same? Deciphering Chinese, Japanese and Koreans by
Fine-Grained Deep Learning | cs.CV | We study to what extend Chinese, Japanese and Korean faces can be classified
and which facial attributes offer the most important cues. First, we propose a
novel way of obtaining large numbers of facial images with nationality labels.
Then we train state-of-the-art neural networks with these labeled images. We
are able... | computer science |
26,369 | Utilizing High-level Visual Feature for Indoor Shopping Mall Navigation | cs.CV | Towards robust and convenient indoor shopping mall navigation, we propose a
novel learning-based scheme to utilize the high-level visual information from
the storefront images captured by personal devices of users. Specifically, we
decompose the visual navigation problem into localization and map generation
respectivel... | computer science |
26,370 | PetroSurf3D - A Dataset for high-resolution 3D Surface Segmentation | cs.CV | The development of powerful 3D scanning hardware and reconstruction
algorithms has strongly promoted the generation of 3D surface reconstructions
in different domains. An area of special interest for such 3D reconstructions
is the cultural heritage domain, where surface reconstructions are generated to
digitally preser... | computer science |
26,371 | Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully
Convolutional Neural Networks and 3D Conditional Random Fields | cs.CV | Automatic segmentation of the liver and its lesion is an important step
towards deriving quantitative biomarkers for accurate clinical diagnosis and
computer-aided decision support systems. This paper presents a method to
automatically segment liver and lesions in CT abdomen images using cascaded
fully convolutional ne... | computer science |
26,372 | Weakly supervised learning of actions from transcripts | cs.CV | We present an approach for weakly supervised learning of human actions from
video transcriptions. Our system is based on the idea that, given a sequence of
input data and a transcript, i.e. a list of the order the actions occur in the
video, it is possible to infer the actions within the video stream, and thus,
learn t... | computer science |
26,373 | Automated Detection of Individual Micro-calcifications from Mammograms
using a Multi-stage Cascade Approach | cs.CV | In mammography, the efficacy of computer-aided detection methods depends, in
part, on the robust localisation of micro-calcifications ($\mu$C). Currently,
the most effective methods are based on three steps: 1) detection of individual
$\mu$C candidates, 2) clustering of individual $\mu$C candidates, and 3)
classificati... | computer science |
26,374 | Learning Grimaces by Watching TV | cs.CV | Differently from computer vision systems which require explicit supervision,
humans can learn facial expressions by observing people in their environment.
In this paper, we look at how similar capabilities could be developed in
machine vision. As a starting point, we consider the problem of relating facial
expressions ... | computer science |
26,375 | Optimization of Convolutional Neural Network using Microcanonical
Annealing Algorithm | cs.CV | Convolutional neural network (CNN) is one of the most prominent architectures
and algorithm in Deep Learning. It shows a remarkable improvement in the
recognition and classification of objects. This method has also been proven to
be very effective in a variety of computer vision and machine learning
problems. As in oth... | computer science |
26,376 | Xception: Deep Learning with Depthwise Separable Convolutions | cs.CV | We present an interpretation of Inception modules in convolutional neural
networks as being an intermediate step in-between regular convolution and the
depthwise separable convolution operation (a depthwise convolution followed by
a pointwise convolution). In this light, a depthwise separable convolution can
be underst... | computer science |
26,377 | Indoor Space Recognition using Deep Convolutional Neural Network: A Case
Study at MIT Campus | cs.CV | In this paper, we propose a robust and parsimonious approach using Deep
Convolutional Neural Network (DCNN) to recognize and interpret interior space.
DCNN has achieved incredible success in object and scene recognition. In this
study we design and train a DCNN to classify a pre-zoning indoor space, and
from a single p... | computer science |
26,378 | ResearchDoom and CocoDoom: Learning Computer Vision with Games | cs.CV | In this short note we introduce ResearchDoom, an implementation of the Doom
first-person shooter that can extract detailed metadata from the game. We also
introduce the CocoDoom dataset, a collection of pre-recorded data extracted
from Doom gaming sessions along with annotations in the MS Coco format.
ResearchDoom and ... | computer science |
26,379 | Content-Based Image Retrieval Using Multiresolution Analysis Of
Shape-Based Classified Images | cs.CV | Content-Based Image Retrieval (CBIR) systems have been widely used for a wide
range of applications such as Art collections, Crime prevention and
Intellectual property. In this paper, a novel CBIR system, which utilizes
visual contents (color, texture and shape) of an image to retrieve images, is
proposed. The proposed... | computer science |
26,380 | Crafting GBD-Net for Object Detection | cs.CV | The visual cues from multiple support regions of different sizes and
resolutions are complementary in classifying a candidate box in object
detection. Effective integration of local and contextual visual cues from these
regions has become a fundamental problem in object detection.
In this paper, we propose a gated bi... | computer science |
26,381 | Learning Spatial-Semantic Context with Fully Convolutional Recurrent
Network for Online Handwritten Chinese Text Recognition | cs.CV | Online handwritten Chinese text recognition (OHCTR) is a challenging problem
as it involves a large-scale character set, ambiguous segmentation, and
variable-length input sequences. In this paper, we exploit the outstanding
capability of path signature to translate online pen-tip trajectories into
informative signature... | computer science |
26,382 | Zero Shot Hashing | cs.CV | This paper provides a framework to hash images containing instances of
unknown object classes. In many object recognition problems, we might have
access to huge amount of data. It may so happen that even this huge data
doesn't cover the objects belonging to classes that we see in our day to day
life. Zero shot learning... | computer science |
26,383 | Egocentric Height Estimation | cs.CV | Egocentric, or first-person vision which became popular in recent years with
an emerge in wearable technology, is different than exocentric (third-person)
vision in some distinguishable ways, one of which being that the camera wearer
is generally not visible in the video frames. Recent work has been done on
action and ... | computer science |
26,384 | Image Segmentation Based on the Self-Balancing Mechanism in Virtual 3D
Elastic Mesh | cs.CV | In this paper, a novel model of 3D elastic mesh is presented for image
segmentation. The model is inspired by stress and strain in physical elastic
objects, while the repulsive force and elastic force in the model are defined
slightly different from the physical force to suit the segmentation problem
well. The self-bal... | computer science |
26,385 | Matching of Images with Rotation Transformation Based on the Virtual
Electromagnetic Interaction | cs.CV | A novel approach of image matching for rotating transformation is presented
and studied. The approach is inspired by electromagnetic interaction force
between physical currents. The virtual current in images is proposed based on
the significant edge lines extracted as the fundamental structural feature of
images. The v... | computer science |
26,386 | Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets | cs.CV | We propose Impatient Deep Neural Networks (DNNs) which deal with dynamic time
budgets during application. They allow for individual budgets given a priori
for each test example and for anytime prediction, i.e., a possible interruption
at multiple stages during inference while still providing output estimates. Our
appro... | computer science |
26,387 | Content Based Image Retrieval (CBIR) in Remote Clinical Diagnosis and
Healthcare | cs.CV | Content-Based Image Retrieval (CBIR) locates, retrieves and displays images
alike to one given as a query, using a set of features. It demands accessible
data in medical archives and from medical equipment, to infer meaning after
some processing. A problem similar in some sense to the target image can aid
clinicians. C... | computer science |
26,388 | Deep Pyramidal Residual Networks | cs.CV | Deep convolutional neural networks (DCNNs) have shown remarkable performance
in image classification tasks in recent years. Generally, deep neural network
architectures are stacks consisting of a large number of convolutional layers,
and they perform downsampling along the spatial dimension via pooling to reduce
memory... | computer science |
26,389 | EM-Based Mixture Models Applied to Video Event Detection | cs.CV | Surveillance system (SS) development requires hi-tech support to prevail over
the shortcomings related to the massive quantity of visual information from
SSs. Anything but reduced human monitoring became impossible by means of its
physical and economic implications, and an advance towards an automated
surveillance beco... | computer science |
26,390 | End-to-end Concept Word Detection for Video Captioning, Retrieval, and
Question Answering | cs.CV | We propose a high-level concept word detector that can be integrated with any
video-to-language models. It takes a video as input and generates a list of
concept words as useful semantic priors for language generation models. The
proposed word detector has two important properties. First, it does not require
any extern... | computer science |
26,391 | Person Re-identification: Past, Present and Future | cs.CV | Person re-identification (re-ID) has become increasingly popular in the
community due to its application and research significance. It aims at spotting
a person of interest in other cameras. In the early days, hand-crafted
algorithms and small-scale evaluation were predominantly reported. Recent years
have witnessed th... | computer science |
26,392 | Learning Low Dimensional Convolutional Neural Networks for
High-Resolution Remote Sensing Image Retrieval | cs.CV | Learning powerful feature representations for image retrieval has always been
a challenging task in the field of remote sensing. Traditional methods focus on
extracting low-level hand-crafted features which are not only time-consuming
but also tend to achieve unsatisfactory performance due to the content
complexity of ... | computer science |
26,393 | FaceVR: Real-Time Facial Reenactment and Eye Gaze Control in Virtual
Reality | cs.CV | We propose FaceVR, a novel image-based method that enables video
teleconferencing in VR based on self-reenactment. State-of-the-art face
tracking methods in the VR context are focused on the animation of rigged 3d
avatars. While they achieve good tracking performance the results look
cartoonish and not real. In contras... | computer science |
26,394 | Multiple Instance Learning Convolutional Neural Networks for Object
Recognition | cs.CV | Convolutional Neural Networks (CNN) have demon- strated its successful
applications in computer vision, speech recognition, and natural language
processing. For object recog- nition, CNNs might be limited by its strict label
requirement and an implicit assumption that images are supposed to be target-
object-dominated ... | computer science |
26,395 | Proposal for Automatic License and Number Plate Recognition System for
Vehicle Identification | cs.CV | In this paper, we propose an automatic and mechanized license and number
plate recognition (LNPR) system which can extract the license plate number of
the vehicles passing through a given location using image processing
algorithms. No additional devices such as GPS or radio frequency identification
(RFID) need to be in... | computer science |
26,396 | Crossing the Road Without Traffic Lights: An Android-based Safety Device | cs.CV | In the absence of pedestrian crossing lights, finding a safe moment to cross
the road is often hazardous and challenging, especially for people with visual
impairments. We present a reliable low-cost solution, an Android device
attached to a traffic sign or lighting pole near the crossing, indicating
whether it is safe... | computer science |
26,397 | Restoring STM images via Sparse Coding: noise and artifact removal | cs.CV | In this article, we present a denoising algorithm to improve the
interpretation and quality of scanning tunneling microscopy (STM) images. Given
the high level of self-similarity of STM images, we propose a denoising
algorithm by reformulating the true estimation problem as a sparse regression,
often termed sparse codi... | computer science |
26,398 | Fused DNN: A deep neural network fusion approach to fast and robust
pedestrian detection | cs.CV | We propose a deep neural network fusion architecture for fast and robust
pedestrian detection. The proposed network fusion architecture allows for
parallel processing of multiple networks for speed. A single shot deep
convolutional network is trained as a object detector to generate all possible
pedestrian candidates o... | computer science |
26,399 | Deep Learning Assessment of Tumor Proliferation in Breast Cancer
Histological Images | cs.CV | Current analysis of tumor proliferation, the most salient prognostic
biomarker for invasive breast cancer, is limited to subjective mitosis counting
by pathologists in localized regions of tissue images. This study presents the
first data-driven integrative approach to characterize the severity of tumor
growth and spre... | computer science |
26,400 | Subspace clustering based on low rank representation and weighted
nuclear norm minimization | cs.CV | Subspace clustering refers to the problem of segmenting a set of data points
approximately drawn from a union of multiple linear subspaces. Aiming at the
subspace clustering problem, various subspace clustering algorithms have been
proposed and low rank representation based subspace clustering is a very
promising and e... | computer science |
26,401 | The Analysis of Local Motion and Deformation in Image Sequences Inspired
by Physical Electromagnetic Interaction | cs.CV | In order to analyze the moving and deforming of the objects in image
sequence, a novel way is presented to analyze the local changes of object edges
between two related images (such as two adjacent frames in a video sequence),
which is inspired by the physical electromagnetic interaction. The changes of
edge between ad... | computer science |
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