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4,100 | Applying Dynamic Model for Multiple Manoeuvring Target Tracking Using
Particle Filtering | cs.CV | In this paper, we applied a dynamic model for manoeuvring targets in SIR
particle filter algorithm for improving tracking accuracy of multiple
manoeuvring targets. In our proposed approach, a color distribution model is
used to detect changes of target's model . Our proposed approach controls
deformation of target's mo... | computer science |
4,101 | An Automatic Algorithm for Object Recognition and Detection Based on
ASIFT Keypoints | cs.AI | Object recognition is an important task in image processing and computer
vision. This paper presents a perfect method for object recognition with full
boundary detection by combining affine scale invariant feature transform
(ASIFT) and a region merging algorithm. ASIFT is a fully affine invariant
algorithm that means f... | computer science |
4,102 | A New Automatic Method to Adjust Parameters for Object Recognition | cs.CV | To recognize an object in an image, the user must apply a combination of
operators, where each operator has a set of parameters. These parameters must
be well adjusted in order to reach good results. Usually, this adjustment is
made manually by the user. In this paper we propose a new method to automate
the process of ... | computer science |
4,103 | An Empirical Study into Annotator Agreement, Ground Truth Estimation,
and Algorithm Evaluation | cs.CV | Although agreement between annotators has been studied in the past from a
statistical viewpoint, little work has attempted to quantify the extent to
which this phenomenon affects the evaluation of computer vision (CV) object
detection algorithms. Many researchers utilise ground truth (GT) in experiments
and more often ... | computer science |
4,104 | Self-Learning for Player Localization in Sports Video | cs.CV | This paper introduces a novel self-learning framework that automates the
label acquisition process for improving models for detecting players in
broadcast footage of sports games. Unlike most previous self-learning
approaches for improving appearance-based object detectors from videos, we
allow an unknown, unconstraine... | computer science |
4,105 | Local Similarities, Global Coding: An Algorithm for Feature Coding and
its Applications | cs.CV | Data coding as a building block of several image processing algorithms has
been received great attention recently. Indeed, the importance of the locality
assumption in coding approaches is studied in numerous works and several
methods are proposed based on this concept. We probe this assumption and claim
that taking th... | computer science |
4,106 | Constraint Reduction using Marginal Polytope Diagrams for MAP LP
Relaxations | cs.CV | LP relaxation-based message passing algorithms provide an effective tool for
MAP inference over Probabilistic Graphical Models. However, different LP
relaxations often have different objective functions and variables of differing
dimensions, which presents a barrier to effective comparison and analysis. In
addition, th... | computer science |
4,107 | Image Processing based Systems and Techniques for the Recognition of
Ancient and Modern Coins | cs.CV | Coins are frequently used in everyday life at various places like in banks,
grocery stores, supermarkets, automated weighing machines, vending machines
etc. So, there is a basic need to automate the counting and sorting of coins.
For this machines need to recognize the coins very fast and accurately, as
further transac... | computer science |
4,108 | Automated Coin Recognition System using ANN | cs.CV | Coins are integral part of our day to day life. We use coins everywhere like
grocery store, banks, buses, trains etc. So it becomes a basic need that coins
can be sorted and counted automatically. For this it is necessary that coins
can be recognized automatically. In this paper we have developed an ANN
(Artificial Neu... | computer science |
4,109 | Rough Clustering Based Unsupervised Image Change Detection | cs.CV | This paper introduces an unsupervised technique to detect the changed region
of multitemporal images on a same reference plane with the help of rough
clustering. The proposed technique is a soft-computing approach, based on the
concept of rough set with rough clustering and Pawlak's accuracy. It is less
noisy and avoid... | computer science |
4,110 | Unsupervised Text Extraction from G-Maps | cs.CV | This paper represents an text extraction method from Google maps, GIS
maps/images. Due to an unsupervised approach there is no requirement of any
prior knowledge or training set about the textual and non-textual parts. Fuzzy
CMeans clustering technique is used for image segmentation and Prewitt method
is used to detect... | computer science |
4,111 | Ambiguity-Driven Fuzzy C-Means Clustering: How to Detect Uncertain
Clustered Records | cs.AI | As a well-known clustering algorithm, Fuzzy C-Means (FCM) allows each input
sample to belong to more than one cluster, providing more flexibility than
non-fuzzy clustering methods. However, the accuracy of FCM is subject to false
detections caused by noisy records, weak feature selection and low certainty of
the algori... | computer science |
4,112 | Sparse distributed localized gradient fused features of objects | cs.CV | The sparse, hierarchical, and modular processing of natural signals is
related to the ability of humans to recognize objects with high accuracy. In
this study, we report a sparse feature processing and encoding method, which
improved the recognition performance of an automated object recognition system.
Randomly distri... | computer science |
4,113 | Fuzzy human motion analysis: A review | cs.CV | Human Motion Analysis (HMA) is currently one of the most popularly active
research domains as such significant research interests are motivated by a
number of real world applications such as video surveillance, sports analysis,
healthcare monitoring and so on. However, most of these real world applications
face high le... | computer science |
4,114 | When Computer Vision Gazes at Cognition | cs.AI | Joint attention is a core, early-developing form of social interaction. It is
based on our ability to discriminate the third party objects that other people
are looking at. While it has been shown that people can accurately determine
whether another person is looking directly at them versus away, little is known
about ... | computer science |
4,115 | Ego-Object Discovery | cs.CV | Lifelogging devices are spreading faster everyday. This growth can represent
great benefits to develop methods for extraction of meaningful information
about the user wearing the device and his/her environment. In this paper, we
propose a semi-supervised strategy for easily discovering objects relevant to
the person we... | computer science |
4,116 | A Large-Scale Car Dataset for Fine-Grained Categorization and
Verification | cs.CV | Updated on 24/09/2015: This update provides preliminary experiment results
for fine-grained classification on the surveillance data of CompCars. The
train/test splits are provided in the updated dataset. See details in Section
6. | computer science |
4,117 | Efficient Convolutional Neural Networks for Pixelwise Classification on
Heterogeneous Hardware Systems | cs.CV | This work presents and analyzes three convolutional neural network (CNN)
models for efficient pixelwise classification of images. When using
convolutional neural networks to classify single pixels in patches of a whole
image, a lot of redundant computations are carried out when using sliding
window networks. This set o... | computer science |
4,118 | Bio-Inspired Human Action Recognition using Hybrid Max-Product
Neuro-Fuzzy Classifier and Quantum-Behaved PSO | cs.AI | Studies on computational neuroscience through functional magnetic resonance
imaging (fMRI) and following biological inspired system stated that human
action recognition in the brain of mammalian leads two distinct pathways in the
model, which are specialized for analysis of motion (optic flow) and form
information. Pri... | computer science |
4,119 | Natural scene statistics mediate the perception of image complexity | cs.AI | Humans are sensitive to complexity and regularity in patterns. The subjective
perception of pattern complexity is correlated to algorithmic
(Kolmogorov-Chaitin) complexity as defined in computer science, but also to the
frequency of naturally occurring patterns. However, the possible mediational
role of natural frequen... | computer science |
4,120 | Learning from Synthetic Data Using a Stacked Multichannel Autoencoder | cs.CV | Learning from synthetic data has many important and practical applications.
An example of application is photo-sketch recognition. Using synthetic data is
challenging due to the differences in feature distributions between synthetic
and real data, a phenomenon we term synthetic gap. In this paper, we
investigate and fo... | computer science |
4,121 | Training Deep Networks with Structured Layers by Matrix Backpropagation | cs.CV | Deep neural network architectures have recently produced excellent results in
a variety of areas in artificial intelligence and visual recognition, well
surpassing traditional shallow architectures trained using hand-designed
features. The power of deep networks stems both from their ability to perform
local computatio... | computer science |
4,122 | Within-Brain Classification for Brain Tumor Segmentation | cs.CV | Purpose: In this paper, we investigate a framework for interactive brain
tumor segmentation which, at its core, treats the problem of interactive brain
tumor segmentation as a machine learning problem.
Methods: This method has an advantage over typical machine learning methods
for this task where generalization is ma... | computer science |
4,123 | Detecting events and key actors in multi-person videos | cs.CV | Multi-person event recognition is a challenging task, often with many people
active in the scene but only a small subset contributing to an actual event. In
this paper, we propose a model which learns to detect events in such videos
while automatically "attending" to the people responsible for the event. Our
model does... | computer science |
4,124 | Discovery Radiomics via StochasticNet Sequencers for Cancer Detection | cs.CV | Radiomics has proven to be a powerful prognostic tool for cancer detection,
and has previously been applied in lung, breast, prostate, and head-and-neck
cancer studies with great success. However, these radiomics-driven methods rely
on pre-defined, hand-crafted radiomic feature sets that can limit their ability
to char... | computer science |
4,125 | Searching for Objects using Structure in Indoor Scenes | cs.CV | To identify the location of objects of a particular class, a passive computer
vision system generally processes all the regions in an image to finally output
few regions. However, we can use structure in the scene to search for objects
without processing the entire image. We propose a search technique that
sequentially... | computer science |
4,126 | Recurrent Instance Segmentation | cs.CV | Instance segmentation is the problem of detecting and delineating each
distinct object of interest appearing in an image. Current instance
segmentation approaches consist of ensembles of modules that are trained
independently of each other, thus missing opportunities for joint learning.
Here we propose a new instance s... | computer science |
4,127 | A Restricted Visual Turing Test for Deep Scene and Event Understanding | cs.CV | This paper presents a restricted visual Turing test (VTT) for story-line
based deep understanding in long-term and multi-camera captured videos. Given a
set of videos of a scene (such as a multi-room office, a garden, and a parking
lot.) and a sequence of story-line based queries, the task is to provide
answers either ... | computer science |
4,128 | Evaluation of Pose Tracking Accuracy in the First and Second Generations
of Microsoft Kinect | cs.CV | Microsoft Kinect camera and its skeletal tracking capabilities have been
embraced by many researchers and commercial developers in various applications
of real-time human movement analysis. In this paper, we evaluate the accuracy
of the human kinematic motion data in the first and second generation of the
Kinect system... | computer science |
4,129 | Remote Health Coaching System and Human Motion Data Analysis for
Physical Therapy with Microsoft Kinect | cs.CV | This paper summarizes the recent progress we have made for the computer
vision technologies in physical therapy with the accessible and affordable
devices. We first introduce the remote health coaching system we build with
Microsoft Kinect. Since the motion data captured by Kinect is noisy, we
investigate the data accu... | computer science |
4,130 | SR-Clustering: Semantic Regularized Clustering for Egocentric Photo
Streams Segmentation | cs.AI | While wearable cameras are becoming increasingly popular, locating relevant
information in large unstructured collections of egocentric images is still a
tedious and time consuming processes. This paper addresses the problem of
organizing egocentric photo streams acquired by a wearable camera into
semantically meaningf... | computer science |
4,131 | Computational Pathology: Challenges and Promises for Tissue Analysis | cs.CV | The histological assessment of human tissue has emerged as the key challenge
for detection and treatment of cancer. A plethora of different data sources
ranging from tissue microarray data to gene expression, proteomics or
metabolomics data provide a detailed overview of the health status of a
patient. Medical doctors ... | computer science |
4,132 | Proactive Message Passing on Memory Factor Networks | cs.AI | We introduce a new type of graphical model that we call a "memory factor
network" (MFN). We show how to use MFNs to model the structure inherent in many
types of data sets. We also introduce an associated message-passing style
algorithm called "proactive message passing"' (PMP) that performs inference on
MFNs. PMP come... | computer science |
4,133 | Online Event Recognition from Moving Vessel Trajectories | cs.CV | We present a system for online monitoring of maritime activity over streaming
positions from numerous vessels sailing at sea. It employs an online tracking
module for detecting important changes in the evolving trajectory of each
vessel across time, and thus can incrementally retain concise, yet reliable
summaries of i... | computer science |
4,134 | Fisher Motion Descriptor for Multiview Gait Recognition | cs.CV | The goal of this paper is to identify individuals by analyzing their gait.
Instead of using binary silhouettes as input data (as done in many previous
works) we propose and evaluate the use of motion descriptors based on densely
sampled short-term trajectories. We take advantage of state-of-the-art people
detectors to ... | computer science |
4,135 | Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects | cs.AI | Human vision greatly benefits from the information about sizes of objects.
The role of size in several visual reasoning tasks has been thoroughly explored
in human perception and cognition. However, the impact of the information about
sizes of objects is yet to be determined in AI. We postulate that this is
mainly attr... | computer science |
4,136 | Visual Genome: Connecting Language and Vision Using Crowdsourced Dense
Image Annotations | cs.CV | Despite progress in perceptual tasks such as image classification, computers
still perform poorly on cognitive tasks such as image description and question
answering. Cognition is core to tasks that involve not just recognizing, but
reasoning about our visual world. However, models used to tackle the rich
content in im... | computer science |
4,137 | SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB
model size | cs.CV | Recent research on deep neural networks has focused primarily on improving
accuracy. For a given accuracy level, it is typically possible to identify
multiple DNN architectures that achieve that accuracy level. With equivalent
accuracy, smaller DNN architectures offer at least three advantages: (1)
Smaller DNNs require... | computer science |
4,138 | Automatic learning of gait signatures for people identification | cs.CV | This work targets people identification in video based on the way they walk
(i.e. gait). While classical methods typically derive gait signatures from
sequences of binary silhouettes, in this work we explore the use of
convolutional neural networks (CNN) for learning high-level descriptors from
low-level motion feature... | computer science |
4,139 | Decision Forests, Convolutional Networks and the Models in-Between | cs.CV | This paper investigates the connections between two state of the art
classifiers: decision forests (DFs, including decision jungles) and
convolutional neural networks (CNNs). Decision forests are computationally
efficient thanks to their conditional computation property (computation is
confined to only a small region o... | computer science |
4,140 | Adaptive Visualisation System for Construction Building Information
Models Using Saliency | cs.CV | Building Information Modeling (BIM) is a recent construction process based on
a 3D model, containing every component related to the building achievement.
Architects, structure engineers, method engineers, and others participant to
the building process work on this model through the design-to-construction
cycle. The hig... | computer science |
4,141 | Neural Aggregation Network for Video Face Recognition | cs.CV | This paper presents a Neural Aggregation Network (NAN) for video face
recognition. The network takes a face video or face image set of a person with
a variable number of face images as its input, and produces a compact,
fixed-dimension feature representation for recognition. The whole network is
composed of two modules... | computer science |
4,142 | Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain
Lesion Segmentation | cs.CV | We propose a dual pathway, 11-layers deep, three-dimensional Convolutional
Neural Network for the challenging task of brain lesion segmentation. The
devised architecture is the result of an in-depth analysis of the limitations
of current networks proposed for similar applications. To overcome the
computational burden o... | computer science |
4,143 | A Comprehensive Performance Evaluation of Deformable Face Tracking
"In-the-Wild" | cs.CV | Recently, technologies such as face detection, facial landmark localisation
and face recognition and verification have matured enough to provide effective
and efficient solutions for imagery captured under arbitrary conditions
(referred to as "in-the-wild"). This is partially attributed to the fact that
comprehensive "... | computer science |
4,144 | A Diagram Is Worth A Dozen Images | cs.CV | Diagrams are common tools for representing complex concepts, relationships
and events, often when it would be difficult to portray the same information
with natural images. Understanding natural images has been extensively studied
in computer vision, while diagram understanding has received little attention.
In this pa... | computer science |
4,145 | Pixel-Level Domain Transfer | cs.CV | We present an image-conditional image generation model. The model transfers
an input domain to a target domain in semantic level, and generates the target
image in pixel level. To generate realistic target images, we employ the
real/fake-discriminator as in Generative Adversarial Nets, but also introduce a
novel domain... | computer science |
4,146 | Building a Large Scale Dataset for Image Emotion Recognition: The Fine
Print and The Benchmark | cs.AI | Psychological research results have confirmed that people can have different
emotional reactions to different visual stimuli. Several papers have been
published on the problem of visual emotion analysis. In particular, attempts
have been made to analyze and predict people's emotional reaction towards
images. To this en... | computer science |
4,147 | Deep Neural Networks Under Stress | cs.CV | In recent years, deep architectures have been used for transfer learning with
state-of-the-art performance in many datasets. The properties of their features
remain, however, largely unstudied under the transfer perspective. In this
work, we present an extensive analysis of the resiliency of feature vectors
extracted f... | computer science |
4,148 | Spontaneous vs. Posed smiles - can we tell the difference? | cs.CV | Smile is an irrefutable expression that shows the physical state of the mind
in both true and deceptive ways. Generally, it shows happy state of the mind,
however, `smiles' can be deceptive, for example people can give a smile when
they feel happy and sometimes they might also give a smile (in a different way)
when the... | computer science |
4,149 | On the equivalence between Kolmogorov-Smirnov and ROC curve metrics for
binary classification | cs.AI | Binary decisions are very common in artificial intelligence. Applying a
threshold on the continuous score gives the human decider the power to control
the operating point to separate the two classes. The classifier,s
discriminating power is measured along the continuous range of the score by the
Area Under the ROC curv... | computer science |
4,150 | Scene Grammars, Factor Graphs, and Belief Propagation | cs.CV | We consider a class of probabilistic grammars for generating scenes with
multiple objects. Probabilistic scene grammars capture relationships between
objects using compositional rules that provide important contextual cues for
inference with ambiguous data. We show how to represent the distribution
defined by a probabi... | computer science |
4,151 | Deep Learning Convolutional Networks for Multiphoton Microscopy
Vasculature Segmentation | cs.CV | Recently there has been an increasing trend to use deep learning frameworks
for both 2D consumer images and for 3D medical images. However, there has been
little effort to use deep frameworks for volumetric vascular segmentation. We
wanted to address this by providing a freely available dataset of 12 annotated
two-phot... | computer science |
4,152 | DISCO Nets: DISsimilarity COefficient Networks | cs.CV | We present a new type of probabilistic model which we call DISsimilarity
COefficient Networks (DISCO Nets). DISCO Nets allow us to efficiently sample
from a posterior distribution parametrised by a neural network. During
training, DISCO Nets are learned by minimising the dissimilarity coefficient
between the true distr... | computer science |
4,153 | Visual-Inertial-Semantic Scene Representation for 3-D Object Detection | cs.CV | We describe a system to detect objects in three-dimensional space using video
and inertial sensors (accelerometer and gyrometer), ubiquitous in modern mobile
platforms from phones to drones. Inertials afford the ability to impose
class-specific scale priors for objects, and provide a global orientation
reference. A min... | computer science |
4,154 | Learning Abstract Classes using Deep Learning | cs.CV | Humans are generally good at learning abstract concepts about objects and
scenes (e.g.\ spatial orientation, relative sizes, etc.). Over the last years
convolutional neural networks have achieved almost human performance in
recognizing concrete classes (i.e.\ specific object categories). This paper
tests the performanc... | computer science |
4,155 | Fully DNN-based Multi-label regression for audio tagging | cs.CV | Acoustic event detection for content analysis in most cases relies on lots of
labeled data. However, manually annotating data is a time-consuming task, which
thus makes few annotated resources available so far. Unlike audio event
detection, automatic audio tagging, a multi-label acoustic event classification
task, only... | computer science |
4,156 | Classification of Alzheimer's Disease Structural MRI Data by Deep
Learning Convolutional Neural Networks | cs.CV | Recently, machine learning techniques especially predictive modeling and
pattern recognition in biomedical sciences from drug delivery system to medical
imaging has become one of the important methods which are assisting researchers
to have deeper understanding of entire issue and to solve complex medical
problems. Dee... | computer science |
4,157 | A Survey of Visual Analysis of Human Motion and Its Applications | cs.CV | This paper summarizes the recent progress in human motion analysis and its
applications. In the beginning, we reviewed the motion capture systems and the
representation model of human's motion data. Next, we sketched the advanced
human motion data processing technologies, including motion data filtering,
temporal align... | computer science |
4,158 | Quick and energy-efficient Bayesian computing of binocular disparity
using stochastic digital signals | cs.CV | Reconstruction of the tridimensional geometry of a visual scene using the
binocular disparity information is an important issue in computer vision and
mobile robotics, which can be formulated as a Bayesian inference problem.
However, computation of the full disparity distribution with an advanced
Bayesian model is usua... | computer science |
4,159 | Places: An Image Database for Deep Scene Understanding | cs.CV | The rise of multi-million-item dataset initiatives has enabled data-hungry
machine learning algorithms to reach near-human semantic classification at
tasks such as object and scene recognition. Here we describe the Places
Database, a repository of 10 million scene photographs, labeled with scene
semantic categories and... | computer science |
4,160 | A Harmonic Mean Linear Discriminant Analysis for Robust Image
Classification | cs.CV | Linear Discriminant Analysis (LDA) is a widely-used supervised dimensionality
reduction method in computer vision and pattern recognition. In null space
based LDA (NLDA), a well-known LDA extension, between-class distance is
maximized in the null space of the within-class scatter matrix. However, there
are some limitat... | computer science |
4,161 | Exploiting inter-image similarity and ensemble of extreme learners for
fixation prediction using deep features | cs.CV | This paper presents a novel fixation prediction and saliency modeling
framework based on inter-image similarities and ensemble of Extreme Learning
Machines (ELM). The proposed framework is inspired by two observations, 1) the
contextual information of a scene along with low-level visual cues modulates
attention, 2) the... | computer science |
4,162 | Template Matching Advances and Applications in Image Analysis | cs.CV | In most computer vision and image analysis problems, it is necessary to
define a similarity measure between two or more different objects or images.
Template matching is a classic and fundamental method used to score
similarities between objects using certain mathematical algorithms. In this
paper, we reviewed the basi... | computer science |
4,163 | Fast Low-rank Shared Dictionary Learning for Image Classification | cs.CV | Despite the fact that different objects possess distinct class-specific
features, they also usually share common patterns. This observation has been
exploited partially in a recently proposed dictionary learning framework by
separating the particularity and the commonality (COPAR). Inspired by this, we
propose a novel ... | computer science |
4,164 | Learning recurrent representations for hierarchical behavior modeling | cs.AI | We propose a framework for detecting action patterns from motion sequences
and modeling the sensory-motor relationship of animals, using a generative
recurrent neural network. The network has a discriminative part (classifying
actions) and a generative part (predicting motion), whose recurrent cells are
laterally conne... | computer science |
4,165 | When Saliency Meets Sentiment: Understanding How Image Content Invokes
Emotion and Sentiment | cs.AI | Sentiment analysis is crucial for extracting social signals from social media
content. Due to the prevalence of images in social media, image sentiment
analysis is receiving increasing attention in recent years. However, most
existing systems are black-boxes that do not provide insight on how image
content invokes sent... | computer science |
4,166 | Learning to detect and localize many objects from few examples | cs.CV | The current trend in object detection and localization is to learn
predictions with high capacity deep neural networks trained on a very large
amount of annotated data and using a high amount of processing power. In this
work, we propose a new neural model which directly predicts bounding box
coordinates. The particula... | computer science |
4,167 | Answering Image Riddles using Vision and Reasoning through Probabilistic
Soft Logic | cs.CV | In this work, we explore a genre of puzzles ("image riddles") which involves
a set of images and a question. Answering these puzzles require both
capabilities involving visual detection (including object, activity
recognition) and, knowledge-based or commonsense reasoning. We compile a
dataset of over 3k riddles where ... | computer science |
4,168 | Invertible Conditional GANs for image editing | cs.CV | Generative Adversarial Networks (GANs) have recently demonstrated to
successfully approximate complex data distributions. A relevant extension of
this model is conditional GANs (cGANs), where the introduction of external
information allows to determine specific representations of the generated
images. In this work, we ... | computer science |
4,169 | Non-Local Color Image Denoising with Convolutional Neural Networks | cs.CV | We propose a novel deep network architecture for grayscale and color image
denoising that is based on a non-local image model. Our motivation for the
overall design of the proposed network stems from variational methods that
exploit the inherent non-local self-similarity property of natural images. We
build on this con... | computer science |
4,170 | Multi-Modal Mean-Fields via Cardinality-Based Clamping | cs.CV | Mean Field inference is central to statistical physics. It has attracted much
interest in the Computer Vision community to efficiently solve problems
expressible in terms of large Conditional Random Fields. However, since it
models the posterior probability distribution as a product of marginal
probabilities, it may fa... | computer science |
4,171 | GuessWhat?! Visual object discovery through multi-modal dialogue | cs.AI | We introduce GuessWhat?!, a two-player guessing game as a testbed for
research on the interplay of computer vision and dialogue systems. The goal of
the game is to locate an unknown object in a rich image scene by asking a
sequence of questions. Higher-level image understanding, like spatial reasoning
and language grou... | computer science |
4,172 | Convolutional Experts Constrained Local Model for Facial Landmark
Detection | cs.CV | Constrained Local Models (CLMs) are a well-established family of methods for
facial landmark detection. However, they have recently fallen out of favor to
cascaded regression-based approaches. This is in part due to the inability of
existing CLM local detectors to model the very complex individual landmark
appearance t... | computer science |
4,173 | SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial
Networks | cs.CV | Autonomous driving is one of the most recent topics of interest which is
aimed at replicating human driving behavior keeping in mind the safety issues.
We approach the problem of learning synthetic driving using generative neural
networks. The main idea is to make a controller trainer network using images
plus key pres... | computer science |
4,174 | Handwriting Profiling using Generative Adversarial Networks | cs.CV | Handwriting is a skill learned by humans from a very early age. The ability
to develop one's own unique handwriting as well as mimic another person's
handwriting is a task learned by the brain with practice. This paper deals with
this very problem where an intelligent system tries to learn the handwriting of
an entity ... | computer science |
4,175 | Context-aware Captions from Context-agnostic Supervision | cs.CV | We introduce an inference technique to produce discriminative context-aware
image captions (captions that describe differences between images or visual
concepts) using only generic context-agnostic training data (captions that
describe a concept or an image in isolation). For example, given images and
captions of "siam... | computer science |
4,176 | LAREX - A semi-automatic open-source Tool for Layout Analysis and Region
Extraction on Early Printed Books | cs.CV | A semi-automatic open-source tool for layout analysis on early printed books
is presented. LAREX uses a rule based connected components approach which is
very fast, easily comprehensible for the user and allows an intuitive manual
correction if necessary. The PageXML format is used to support integration into
existing ... | computer science |
4,177 | Learning an attention model in an artificial visual system | cs.CV | The Human visual perception of the world is of a large fixed image that is
highly detailed and sharp. However, receptor density in the retina is not
uniform: a small central region called the fovea is very dense and exhibits
high resolution, whereas a peripheral region around it has much lower spatial
resolution. Thus,... | computer science |
4,178 | View Independent Vehicle Make, Model and Color Recognition Using
Convolutional Neural Network | cs.CV | This paper describes the details of Sighthound's fully automated vehicle
make, model and color recognition system. The backbone of our system is a deep
convolutional neural network that is not only computationally inexpensive, but
also provides state-of-the-art results on several competitive benchmarks.
Additionally, o... | computer science |
4,179 | DAGER: Deep Age, Gender and Emotion Recognition Using Convolutional
Neural Network | cs.CV | This paper describes the details of Sighthound's fully automated age, gender
and emotion recognition system. The backbone of our system consists of several
deep convolutional neural networks that are not only computationally
inexpensive, but also provide state-of-the-art results on several competitive
benchmarks. To po... | computer science |
4,180 | Visualizing Deep Neural Network Decisions: Prediction Difference
Analysis | cs.CV | This article presents the prediction difference analysis method for
visualizing the response of a deep neural network to a specific input. When
classifying images, the method highlights areas in a given input image that
provide evidence for or against a certain class. It overcomes several
shortcoming of previous method... | computer science |
4,181 | Automatic Liver and Tumor Segmentation of CT and MRI Volumes using
Cascaded Fully Convolutional Neural Networks | cs.CV | Automatic segmentation of the liver and hepatic lesions 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 and MRI abdomen images using
cascaded fully con... | computer science |
4,182 | Unsupervised Diverse Colorization via Generative Adversarial Networks | cs.CV | Colorization of grayscale images has been a hot topic in computer vision.
Previous research mainly focuses on producing a colored image to match the
original one. However, since many colors share the same gray value, an input
grayscale image could be diversely colored while maintaining its reality. In
this paper, we de... | computer science |
4,183 | Asymmetric Tri-training for Unsupervised Domain Adaptation | cs.CV | Deep-layered models trained on a large number of labeled samples boost the
accuracy of many tasks. It is important to apply such models to different
domains because collecting many labeled samples in various domains is
expensive. In unsupervised domain adaptation, one needs to train a classifier
that works well on a ta... | computer science |
4,184 | Unsupervised Image-to-Image Translation Networks | cs.CV | Unsupervised image-to-image translation aims at learning a joint distribution
of images in different domains by using images from the marginal distributions
in individual domains. Since there exists an infinite set of joint
distributions that can arrive the given marginal distributions, one could infer
nothing about th... | computer science |
4,185 | High-Resolution Multispectral Dataset for Semantic Segmentation | cs.CV | Unmanned aircraft have decreased the cost required to collect remote sensing
imagery, which has enabled researchers to collect high-spatial resolution data
from multiple sensor modalities more frequently and easily. The increase in
data will push the need for semantic segmentation frameworks that are able to
classify n... | computer science |
4,186 | Gait Pattern Recognition Using Accelerometers | cs.CV | Motion ability is one of the most important human properties, including gait
as a basis of human transitional movement. Gait, as a biometric for recognizing
human identities, can be non-intrusively captured signals using wearable or
portable smart devices. In this study gait patterns is collected using a
wireless platf... | computer science |
4,187 | Expecting the Unexpected: Training Detectors for Unusual Pedestrians
with Adversarial Imposters | cs.CV | As autonomous vehicles become an every-day reality, high-accuracy pedestrian
detection is of paramount practical importance. Pedestrian detection is a
highly researched topic with mature methods, but most datasets focus on common
scenes of people engaged in typical walking poses on sidewalks. But performance
is most cr... | computer science |
4,188 | Algorithms for Semantic Segmentation of Multispectral Remote Sensing
Imagery using Deep Learning | cs.CV | Deep convolutional neural networks (DCNNs) have been used to achieve
state-of-the-art performance on many computer vision tasks (e.g., object
recognition, object detection, semantic segmentation) thanks to a large
repository of annotated image data. Large labeled datasets for other sensor
modalities, e.g., multispectra... | computer science |
4,189 | Object category understanding via eye fixations on freehand sketches | cs.CV | The study of eye gaze fixations on photographic images is an active research
area. In contrast, the image subcategory of freehand sketches has not received
as much attention for such studies. In this paper, we analyze the results of a
free-viewing gaze fixation study conducted on 3904 freehand sketches
distributed acro... | computer science |
4,190 | Open Vocabulary Scene Parsing | cs.CV | Recognizing arbitrary objects in the wild has been a challenging problem due
to the limitations of existing classification models and datasets. In this
paper, we propose a new task that aims at parsing scenes with a large and open
vocabulary, and several evaluation metrics are explored for this problem. Our
proposed ap... | computer science |
4,191 | Quality Aware Network for Set to Set Recognition | cs.CV | This paper targets on the problem of set to set recognition, which learns the
metric between two image sets. Images in each set belong to the same identity.
Since images in a set can be complementary, they hopefully lead to higher
accuracy in practical applications. However, the quality of each sample cannot
be guarant... | computer science |
4,192 | Deep Reinforcement Learning-based Image Captioning with Embedding Reward | cs.CV | Image captioning is a challenging problem owing to the complexity in
understanding the image content and diverse ways of describing it in natural
language. Recent advances in deep neural networks have substantially improved
the performance of this task. Most state-of-the-art approaches follow an
encoder-decoder framewo... | computer science |
4,193 | Virtual to Real Reinforcement Learning for Autonomous Driving | cs.AI | Reinforcement learning is considered as a promising direction for driving
policy learning. However, training autonomous driving vehicle with
reinforcement learning in real environment involves non-affordable
trial-and-error. It is more desirable to first train in a virtual environment
and then transfer to the real envi... | computer science |
4,194 | OCRAPOSE II: An OCR-based indoor positioning system using mobile phone
images | cs.CV | In this paper, we propose an OCR (optical character recognition)-based
localization system called OCRAPOSE II, which is applicable in a number of
indoor scenarios including office buildings, parkings, airports, grocery
stores, etc. In these scenarios, characters (i.e. texts or numbers) can be used
as suitable distincti... | computer science |
4,195 | Network Dissection: Quantifying Interpretability of Deep Visual
Representations | cs.CV | We propose a general framework called Network Dissection for quantifying the
interpretability of latent representations of CNNs by evaluating the alignment
between individual hidden units and a set of semantic concepts. Given any CNN
model, the proposed method draws on a broad data set of visual concepts to
score the s... | computer science |
4,196 | A Review on Deep Learning Techniques Applied to Semantic Segmentation | cs.CV | Image semantic segmentation is more and more being of interest for computer
vision and machine learning researchers. Many applications on the rise need
accurate and efficient segmentation mechanisms: autonomous driving, indoor
navigation, and even virtual or augmented reality systems to name a few. This
demand coincide... | computer science |
4,197 | Towards Instance Segmentation with Object Priority: Prominent Object
Detection and Recognition | cs.CV | This manuscript introduces the problem of prominent object detection and
recognition inspired by the fact that human seems to priorities perception of
scene elements. The problem deals with finding the most important region of
interest, segmenting the relevant item/object in that area, and assigning it an
object class ... | computer science |
4,198 | Paying Attention to Descriptions Generated by Image Captioning Models | cs.CV | To bridge the gap between humans and machines in image understanding and
describing, we need further insight into how people describe a perceived scene.
In this paper, we study the agreement between bottom-up saliency-based visual
attention and object referrals in scene description constructs. We investigate
the proper... | computer science |
4,199 | No More Discrimination: Cross City Adaptation of Road Scene Segmenters | cs.CV | Despite the recent success of deep-learning based semantic segmentation,
deploying a pre-trained road scene segmenter to a city whose images are not
presented in the training set would not achieve satisfactory performance due to
dataset biases. Instead of collecting a large number of annotated images of
each city of in... | computer science |
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