Computer Vision – ECCV 2020

Table of Contents

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   Book Overview
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   Chapter 1 EfficientFCN: Holistically-Guided Decoding for Semantic Segmentation
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   Chapter 2 GroSS: Group-Size Series Decomposition for Grouped Architecture Search
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   Chapter 3 Efficient Adversarial Attacks for Visual Object Tracking
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   Chapter 4 Globally-Optimal Event Camera Motion Estimation
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   Chapter 5 Weakly-Supervised Learning of Human Dynamics
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   Chapter 6 Journey Towards Tiny Perceptual Super-Resolution
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   Chapter 7 What Makes Fake Images Detectable? Understanding Properties that Generalize
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   Chapter 8 Embedding Propagation: Smoother Manifold for Few-Shot Classification
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    Chapter 9 Category Level Object Pose Estimation via Neural Analysis-by-Synthesis
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    Chapter 10 High-Fidelity Synthesis with Disentangled Representation
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    Chapter 11 PL$$_1$$P - Point-Line Minimal Problems Under Partial Visibility in Three Views
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    Chapter 12 Prediction and Recovery for Adaptive Low-Resolution Person Re-Identification
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    Chapter 13 Learning Canonical Representations for Scene Graph to Image Generation
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    Chapter 14 Adversarial Robustness on In- and Out-Distribution Improves Explainability
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    Chapter 15 Deformable Style Transfer
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    Chapter 16 Aligning Videos in Space and Time
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    Chapter 17 Neural Wireframe Renderer: Learning Wireframe to Image Translations
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    Chapter 18 RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax
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    Chapter 19 Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction
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    Chapter 20 Determining the Relevance of Features for Deep Neural Networks
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    Chapter 21 Weakly Supervised Semantic Segmentation with Boundary Exploration
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    Chapter 22 GANHopper: Multi-hop GAN for Unsupervised Image-to-Image Translation
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    Chapter 23 DOPE: Distillation of Part Experts for Whole-Body 3D Pose Estimation in the Wild
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    Chapter 24 Multi-view Adaptive Graph Convolutions for Graph Classification
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    Chapter 25 Instance Adaptive Self-training for Unsupervised Domain Adaptation
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    Chapter 26 Weight Decay Scheduling and Knowledge Distillation for Active Learning
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    Chapter 27 HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs
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    Chapter 28 Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning
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    Chapter 29 Geometry Constrained Weakly Supervised Object Localization
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    Chapter 30 Duality Diagram Similarity: A Generic Framework for Initialization Selection in Task Transfer Learning
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    Chapter 31 OneGAN: Simultaneous Unsupervised Learning of Conditional Image Generation, Foreground Segmentation, and Fine-Grained Clustering
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    Chapter 32 Mining Self-similarity: Label Super-Resolution with Epitomic Representations
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    Chapter 33 AE-OT-GAN: Training GANs from Data Specific Latent Distribution
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    Chapter 34 Null-Sampling for Interpretable and Fair Representations
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    Chapter 35 Guiding Monocular Depth Estimation Using Depth-Attention Volume
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    Chapter 36 Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping
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    Chapter 37 Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer
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    Chapter 38 BézierSketch: A Generative Model for Scalable Vector Sketches
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    Chapter 39 Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation
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    Chapter 40 Domain Adaptation Through Task Distillation
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    Chapter 41 PatchAttack: A Black-Box Texture-Based Attack with Reinforcement Learning
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    Chapter 42 More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning
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    Chapter 43 Extending and Analyzing Self-supervised Learning Across Domains
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    Chapter 44 Multi-source Open-Set Deep Adversarial Domain Adaptation
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    Chapter 45 Neural Batch Sampling with Reinforcement Learning for Semi-supervised Anomaly Detection
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    Chapter 46 LEMMA: A Multi-view Dataset for L Earning Multi-agent Multi-task Activities