Computer vision -- ECCV 2020 : 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings. Part IV / Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm (eds.).

Intro
Foreword
Preface
Organization
Contents
Part IV
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors
1 Introduction
2 Related Work
2.1 Object Detector Basics
3 Approach
3.1 Creating a Universal Adversarial Patch
4 Crafting Attacks in the Digital World
4.1 Evaluation of Digital Attacks
5 Physical World Attacks
5.1 Printed Posters
5.2 Paper Dolls
6 Wearable Adversarial Examples
7 Conclusion
References
TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images
1 Introduction

2 Related Works
2.1 Image-to-Image Translation
2.2 Image Style Transfer
2.3 Single Image Generative Models
3 Method
3.1 Network Architecture
3.2 Loss Functions
3.3 Implementation Details
4 Experiments
4.1 Baselines
4.2 Evaluation Metrics
4.3 Results
4.4 Ablation Study
5 Conclusion
References
Semi-Siamese Training for Shallow Face Learning
1 Introduction
2 Related Work
2.1 Deep Face Recognition
2.2 Low-Shot Face Recognition
2.3 Self-supervised Learning
3 The Proposed Approach
3.1 Shallow Face Learning Problem

3.2 Semi-Siamese Training
4 Experiments
4.1 Datasets and Experimental Settings
4.2 Ablation Study
4.3 SST with Various Loss Functions
4.4 SST with Various Network Architectures
4.5 SST on Deep Data Learning
4.6 Pretrain and Finetune
5 Conclusions
References
GAN Slimming: All-in-One GAN Compression by a Unified Optimization Framework
1 Introduction
2 Related Works
2.1 Deep Model Compression
2.2 GAN Compression
3 The GAN Slimming Framework
3.1 The Unified Optimization Form
3.2 End-to-End Optimization
3.3 Algorithm Implementation
4 Experiments

4.1 Unpaired Image Translation with CycleGAN
4.2 Ablation Study
4.3 Real-World Application: CartoonGAN
5 Conclusion
A Image Generation with SNGAN
References
Human Interaction Learning on 3D Skeleton Point Clouds for Video Violence Recognition
1 Introduction
2 Related Work
3 Proposed Method
3.1 Framework
3.2 Skeleton Points Interaction Learning Module
3.3 Multi-head Mechanism
3.4 Skeleton Point Convolution
4 Experiments
4.1 Ablation Study
4.2 Comparison with the State of the Art
4.3 Failure Case
5 Conclusion
References

Binarized Neural Network for Single Image Super Resolution
1 Introduction
2 Related Work
2.1 Single Image Super Resolution
2.2 Quantitative Model
3 Proposed Approach
3.1 Motivation
3.2 Quantization of Weights
3.3 Quantization of Activations
3.4 Binary Super Resolution Network
4 Experiments
4.1 Datasets
4.2 Implementations
4.3 Evaluation
4.4 Model Analysis
5 Conclusions
References
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation
1 Introduction
2 Related Work
3 Method
3.1 Position-Sensitive Self-attention