Computer Vision – ECCV 2022

Table of Contents

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   Book Overview
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   Chapter 1 Fast Two-View Motion Segmentation Using Christoffel Polynomials
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   Chapter 2 UCTNet: Uncertainty-Aware Cross-Modal Transformer Network for Indoor RGB-D Semantic Segmentation
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   Chapter 3 Bi-directional Contrastive Learning for Domain Adaptive Semantic Segmentation
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   Chapter 4 Learning Regional Purity for Instance Segmentation on 3D Point Clouds
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   Chapter 5 Cross-Domain Few-Shot Semantic Segmentation
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   Chapter 6 Generative Subgraph Contrast for Self-Supervised Graph Representation Learning
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   Chapter 7 SdAE: Self-distillated Masked Autoencoder
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   Chapter 8 Demystifying Unsupervised Semantic Correspondence Estimation
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    Chapter 9 Open-Set Semi-Supervised Object Detection
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    Chapter 10 Vibration-Based Uncertainty Estimation for Learning from Limited Supervision
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    Chapter 11 Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
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    Chapter 12 Weakly Supervised Object Localization Through Inter-class Feature Similarity and Intra-class Appearance Consistency
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    Chapter 13 Active Learning Strategies for Weakly-Supervised Object Detection
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    Chapter 14 mc-BEiT: Multi-choice Discretization for Image BERT Pre-training
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    Chapter 15 Bootstrapped Masked Autoencoders for Vision BERT Pretraining
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    Chapter 16 Unsupervised Visual Representation Learning by Synchronous Momentum Grouping
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    Chapter 17 Improving Few-Shot Part Segmentation Using Coarse Supervision
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    Chapter 18 What to Hide from Your Students: Attention-Guided Masked Image Modeling
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    Chapter 19 Pointly-Supervised Panoptic Segmentation
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    Chapter 20 MVP: Multimodality-Guided Visual Pre-training
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    Chapter 21 Locally Varying Distance Transform for Unsupervised Visual Anomaly Detection
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    Chapter 22 HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
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    Chapter 23 SPot-the-Difference Self-supervised Pre-training for Anomaly Detection and Segmentation
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    Chapter 24 Dual-Domain Self-supervised Learning and Model Adaption for Deep Compressive Imaging
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    Chapter 25 Unsupervised Selective Labeling for More Effective Semi-supervised Learning
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    Chapter 26 Max Pooling with Vision Transformers Reconciles Class and Shape in Weakly Supervised Semantic Segmentation
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    Chapter 27 Dense Siamese Network for Dense Unsupervised Learning
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    Chapter 28 Multi-granularity Distillation Scheme Towards Lightweight Semi-supervised Semantic Segmentation
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    Chapter 29 CP$$^2$$: Copy-Paste Contrastive Pretraining for Semantic Segmentation
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    Chapter 30 Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization
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    Chapter 31 RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning
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    Chapter 32 MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation
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    Chapter 33 United Defocus Blur Detection and Deblurring via Adversarial Promoting Learning
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    Chapter 34 Synergistic Self-supervised and Quantization Learning
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    Chapter 35 Semi-supervised Vision Transformers
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    Chapter 36 Domain Adaptive Video Segmentation via Temporal Pseudo Supervision
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    Chapter 37 Diverse Learner: Exploring Diverse Supervision for Semi-supervised Object Detection
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    Chapter 38 A Closer Look at Invariances in Self-supervised Pre-training for 3D Vision
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    Chapter 39 ConMatch: Semi-supervised Learning with Confidence-Guided Consistency Regularization
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    Chapter 40 FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
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    Chapter 41 W2N: Switching from Weak Supervision to Noisy Supervision for Object Detection
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    Chapter 42 Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness