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Computer Vision – ECCV 2022

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Table of Contents

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    Book Overview
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    Chapter 1 Relative Contrastive Loss for Unsupervised Representation Learning
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    Chapter 2 Fine-Grained Fashion Representation Learning by Online Deep Clustering
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    Chapter 3 NashAE: Disentangling Representations Through Adversarial Covariance Minimization
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    Chapter 4 A Gyrovector Space Approach for Symmetric Positive Semi-definite Matrix Learning
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    Chapter 5 Learning Visual Representation from Modality-Shared Contrastive Language-Image Pre-training
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    Chapter 6 Contrasting Quadratic Assignments for Set-Based Representation Learning
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    Chapter 7 Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer
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    Chapter 8 Object Discovery and Representation Networks
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    Chapter 9 Trading Positional Complexity vs Deepness in Coordinate Networks
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    Chapter 10 MVDG: A Unified Multi-view Framework for Domain Generalization
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    Chapter 11 Panoptic Scene Graph Generation
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    Chapter 12 Object-Compositional Neural Implicit Surfaces
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    Chapter 13 RigNet: Repetitive Image Guided Network for Depth Completion
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    Chapter 14 FADE: Fusing the Assets of Decoder and Encoder for Task-Agnostic Upsampling
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    Chapter 15 LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
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    Chapter 16 Hierarchical Memory Learning for Fine-Grained Scene Graph Generation
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    Chapter 17 DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
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    Chapter 18 MTFormer: Multi-task Learning via Transformer and Cross-Task Reasoning
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    Chapter 19 MonoPLFlowNet: Permutohedral Lattice FlowNet for Real-Scale 3D Scene Flow Estimation with Monocular Images
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    Chapter 20 TO-Scene: A Large-Scale Dataset for Understanding 3D Tabletop Scenes
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    Chapter 21 Is It Necessary to Transfer Temporal Knowledge for Domain Adaptive Video Semantic Segmentation?
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    Chapter 22 Meta Spatio-Temporal Debiasing for Video Scene Graph Generation
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    Chapter 23 Improving the Reliability for Confidence Estimation
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    Chapter 24 Fine-Grained Scene Graph Generation with Data Transfer
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    Chapter 25 Pose2Room: Understanding 3D Scenes from Human Activities
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    Chapter 26 Towards Hard-Positive Query Mining for DETR-Based Human-Object Interaction Detection
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    Chapter 27 Discovering Human-Object Interaction Concepts via Self-Compositional Learning
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    Chapter 28 Primitive-Based Shape Abstraction via Nonparametric Bayesian Inference
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    Chapter 29 Stereo Depth Estimation with Echoes
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    Chapter 30 Inverted Pyramid Multi-task Transformer for Dense Scene Understanding
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    Chapter 31 PETR: Position Embedding Transformation for Multi-view 3D Object Detection
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    Chapter 32 S2Net: Stochastic Sequential Pointcloud Forecasting
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    Chapter 33 RA-Depth: Resolution Adaptive Self-supervised Monocular Depth Estimation
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    Chapter 34 PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation
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    Chapter 35 SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds
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    Chapter 36 PointMixer: MLP-Mixer for Point Cloud Understanding
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    Chapter 37 Initialization and Alignment for Adversarial Texture Optimization
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    Chapter 38 MOTR: End-to-End Multiple-Object Tracking with Transformer
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    Chapter 39 GALA: Toward Geometry-and-Lighting-Aware Object Search for Compositing
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    Chapter 40 LaLaLoc++: Global Floor Plan Comprehension for Layout Localisation in Unvisited Environments
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    Chapter 41 3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling
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    Chapter 42 Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentation
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Title
Computer Vision – ECCV 2022
Published by
Springer Nature Switzerland, October 2022
DOI 10.1007/978-3-031-19812-0
ISBNs
978-3-03-119811-3, 978-3-03-119812-0
Editors

Avidan, Shai, Brostow, Gabriel, Cissé, Moustapha, Farinella, Giovanni Maria, Hassner, Tal

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