Computer Vision – ACCV 2020

Table of Contents

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   Book Overview
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   Chapter 1 End-to-End Model-Based Gait Recognition
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   Chapter 2 Horizontal Flipping Assisted Disentangled Feature Learning for Semi-supervised Person Re-identification
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   Chapter 3 MIX’EM: Unsupervised Image Classification Using a Mixture of Embeddings
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   Chapter 4 Backbone Based Feature Enhancement for Object Detection
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   Chapter 5 Long-Term Cloth-Changing Person Re-identification
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   Chapter 6 Any-Shot Object Detection
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   Chapter 7 Background Learnable Cascade for Zero-Shot Object Detection
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   Chapter 8 Unsupervised Domain Adaptive Object Detection Using Forward-Backward Cyclic Adaptation
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    Chapter 9 COG: COnsistent Data AuGmentation for Object Perception
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    Chapter 10 Synthesizing the Unseen for Zero-Shot Object Detection
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    Chapter 11 Fully Supervised and Guided Distillation for One-Stage Detectors
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    Chapter 12 Visualizing Color-Wise Saliency of Black-Box Image Classification Models
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    Chapter 13 ERIC: Extracting Relations Inferred from Convolutions
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    Chapter 14 D2D: Keypoint Extraction with Describe to Detect Approach
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    Chapter 15 Accurate Arbitrary-Shaped Scene Text Detection via Iterative Polynomial Parameter Regression
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    Chapter 16 Adaptive Spotting: Deep Reinforcement Object Search in 3D Point Clouds
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    Chapter 17 Efficient Large-Scale Semantic Visual Localization in 2D Maps
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    Chapter 18 Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild
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    Chapter 19 Scale-Aware Polar Representation for Arbitrarily-Shaped Text Detection
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    Chapter 20 Branch Interaction Network for Person Re-identification
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    Chapter 21 BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images
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    Chapter 22 Jointly Discriminating and Frequent Visual Representation Mining
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    Chapter 23 Discrete Spatial Importance-Based Deep Weighted Hashing
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    Chapter 24 Low-Level Sensor Fusion for 3D Vehicle Detection Using Radar Range-Azimuth Heatmap and Monocular Image
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    Chapter 25 MLIFeat: Multi-level Information Fusion Based Deep Local Features
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    Chapter 26 CLASS: Cross-Level Attention and Supervision for Salient Objects Detection
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    Chapter 27 Cascaded Transposed Long-Range Convolutions for Monocular Depth Estimation
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    Chapter 28 Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks
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    Chapter 29 Large-Scale Cross-Domain Few-Shot Learning
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    Chapter 30 Channel Pruning for Accelerating Convolutional Neural Networks via Wasserstein Metric
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    Chapter 31 Progressive Batching for Efficient Non-linear Least Squares
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    Chapter 32 Fast and Differentiable Message Passing on Pairwise Markov Random Fields
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    Chapter 33 A Calibration Method for the Generalized Imaging Model with Uncertain Calibration Target Coordinates
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    Chapter 34 Graph-Based Heuristic Search for Module Selection Procedure in Neural Module Network
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    Chapter 35 Towards Fast and Robust Adversarial Training for Image Classification
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    Chapter 36 Few-Shot Zero-Shot Learning: Knowledge Transfer with Less Supervision
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    Chapter 37 Lossless Image Compression Using a Multi-scale Progressive Statistical Model
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    Chapter 38 Spatial Class Distribution Shift in Unsupervised Domain Adaptation: Local Alignment Comes to Rescue
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    Chapter 39 Point Proposal Based Instance Segmentation with Rectangular Masks for Robot Picking Task
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    Chapter 40 Multi-task Learning with Future States for Vision-Based Autonomous Driving
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    Chapter 41 MTNAS: Search Multi-task Networks for Autonomous Driving
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    Chapter 42 Compact and Fast Underwater Segmentation Network for Autonomous Underwater Vehicles
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    Chapter 43 L2R GAN: LiDAR-to-Radar Translation
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    Chapter 44 V2A - Vision to Action: Learning Robotic Arm Actions Based on Vision and Language
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    Chapter 45 To Filter Prune, or to Layer Prune, That Is the Question