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Chapter and Conference Paper
The Sixth Visual Object Tracking VOT2018 Challenge Results
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers...
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Chapter and Conference Paper
Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis
Autism spectrum disorder (ASD) is mainly diagnosed by the observation of core behavioral symptoms. Due to the absence of early biomarkers to detect infants either with or at-risk of ASD during the first postnatal...
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Chapter and Conference Paper
Learning to Navigate for Fine-Grained Classification
Fine-grained classification is challenging due to the difficulty of finding discriminative features. Finding those subtle traits that fully characterize the object is not straightforward. To handle this circum...
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Chapter and Conference Paper
Real-Time ‘Actor-Critic’ Tracking
In this work, we propose a novel tracking algorithm with real-time performance based on the ‘Actor-Critic’ framework. This framework consists of two major components: ‘Actor’ and ‘Critic’. The ‘Actor’ model ai...
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Chapter and Conference Paper
Deep Gabor Scattering Network for Image Classification
Deep learning models obtain exponential ascension in the field of image classification in recent years, and have become the most active research branch in AI research. The success of deep learning prompts us t...
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Chapter and Conference Paper
Shot Boundary Detection with Spatial-Temporal Convolutional Neural Networks
Nowadays, digital videos have been widely leveraged to record and share various events and people’s daily life. It becomes urgent to provide automatic video semantic analysis and management for convenience. Sh...
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Chapter and Conference Paper
Towards Automatic Semantic Segmentation in Volumetric Ultrasound
3D ultrasound is rapidly emerging as a viable imaging modality for routine prenatal examinations. However, lacking of efficient tools to decompose the volumetric data greatly limits its widespread. In this pap...
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Chapter and Conference Paper
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
Computed tomography (CT) is critical for various clinical applications, e.g., radiation treatment planning and also PET attenuation correction in MRI/PET scanner. However, CT exposes radiation during acquisiti...
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Chapter and Conference Paper
Deformable Image Registration Based on Similarity-Steered CNN Regression
Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based method...
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Chapter and Conference Paper
Multi-context Deep Convolutional Features and Exemplar-SVMs for Scene Parsing
Scene parsing is a challenging task in computer vision field. The work of scene parsing is labeling every pixel in an image with its semantic category to which it belongs. In this paper, we solve this problem ...
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Chapter and Conference Paper
Image Forgery Detection Based on Semantic Image Understanding
Image forensics has been focusing on low-level visual features, paying little attention to high-level semantic information of the image. In this work, we propose the framework for image forgery detection based...
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Chapter and Conference Paper
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
3D action recognition – analysis of human actions based on 3D skeleton data – becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recent attempts on this problem su...
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Chapter and Conference Paper
A Siamese Long Short-Term Memory Architecture for Human Re-identification
Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance. In the existing works concentrating on feature extraction...
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Chapter and Conference Paper
Unsupervised Visual Representation Learning by Graph-Based Consistent Constraints
Learning rich visual representations often require training on datasets of millions of manually annotated examples. This substantially limits the scalability of learning effective representations as labeled da...
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Chapter and Conference Paper
Hierarchical Convolutional Neural Network for Face Detection
In this paper, we propose a new approach of hierarchical convolutional neural network (CNN) for face detection. The first layer of our architecture is a binary classifier built on a deep convolutional neural n...
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Chapter and Conference Paper
One Simple Virtual Avatar System Based on Single Image
To establish virtual avatar systems at the computing environments with limited resources, we design such a system based on single image which can generate speech animation with different facial expressions. Fi...
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Chapter and Conference Paper
Sequential Max-Margin Event Detectors
Many applications in computer vision (e.g., games, human computer interaction) require a reliable and early detector of visual events. Existing event detection methods rely on one-versus-all or multi-class cla...
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Chapter and Conference Paper
Reasoning about Semantic Web Services with an Approach Based on Temporal Description Logic
Temporal description logic ALC-LTL not only has considerable expressive power, but also extends the description capability of description logic from the static domain to the dynamic domain. In this paper, ALC-LTL...
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Chapter and Conference Paper
Bayesian Face Revisited: A Joint Formulation
In this paper, we revisit the classical Bayesian face recognition method by Baback Moghaddam et al. and propose a new joint formulation. The classical Bayesian method models the appearance difference between t...
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Chapter and Conference Paper
Outdoor Face Recognition Using Enhanced Near Infrared Imaging
In this paper, we present a robust and accurate system for outdoor (as well as indoor) face recognition, based on a recently developed enhanced near-infrared (ENIR) imaging device. Using a narrow band NIR lase...