Computer Vision – ACCV 2016

Table of Contents

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   Book Overview
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   Chapter 1 Sparse Code Filtering for Action Pattern Mining
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   Chapter 2 Learning Action Concept Trees and Semantic Alignment Networks from Image-Description Data
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   Chapter 3 Pedestrian Color Naming via Convolutional Neural Network
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   Chapter 4 Speed Invariance vs. Stability: Cross-Speed Gait Recognition Using Single-Support Gait Energy Image
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   Chapter 5 Parametric Image Segmentation of Humans with Structural Shape Priors
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   Chapter 6 Lip Reading in the Wild
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   Chapter 7 Recurrent Convolutional Face Alignment
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   Chapter 8 Continuous Supervised Descent Method for Facial Landmark Localisation
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    Chapter 9 Modeling Stylized Character Expressions via Deep Learning
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    Chapter 10 Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units
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    Chapter 11 Multi-Instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation
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    Chapter 12 Analysis on the Dropout Effect in Convolutional Neural Networks
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    Chapter 13 Efficient Model Averaging for Deep Neural Networks
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    Chapter 14 Joint Training of Generic CNN-CRF Models with Stochastic Optimization
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    Chapter 15 Object-Aware Dictionary Learning with Deep Features
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    Chapter 16 Gait Energy Response Function for Clothing-Invariant Gait Recognition
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    Chapter 17 Action Recognition Based on Optimal Joint Selection and Discriminative Depth Descriptor
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    Chapter 18 Model-Free Multiple Object Tracking with Shared Proposals
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    Chapter 19 Learning to Integrate Occlusion-Specific Detectors for Heavily Occluded Pedestrian Detection
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    Chapter 20 Deep Second-Order Siamese Network for Pedestrian Re-identification
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    Chapter 21 Cost-Sensitive Two-Stage Depression Prediction Using Dynamic Visual Clues
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    Chapter 22 Human Interaction Recognition by Mining Discriminative Patches on Key Frames
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    Chapter 23 Stacked Overcomplete Independent Component Analysis for Action Recognition
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    Chapter 24 Searching Action Proposals via Spatial Actionness Estimation and Temporal Path Inference and Tracking
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    Chapter 25 Markov Chain Monte Carlo Cascade for Camera Network Calibration Based on Unconstrained Pedestrian Tracklets
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    Chapter 26 Scale-Adaptive Deconvolutional Regression Network for Pedestrian Detection