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Computer Vision – ECCV 2022

Overview of attention for book
Computer Vision – ECCV 2022
Springer Nature Switzerland

Table of Contents

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    Book Overview
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    Chapter 1 Interpretable Open-Set Domain Adaptation via Angular Margin Separation
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    Chapter 3 Prototypical Contrast Adaptation for Domain Adaptive Semantic Segmentation
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    Chapter 4 RBC: Rectifying the Biased Context in Continual Semantic Segmentation
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    Chapter 5 Factorizing Knowledge in Neural Networks
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    Chapter 6 Contrastive Vicinal Space for Unsupervised Domain Adaptation
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    Chapter 7 Cross-Modal Knowledge Transfer Without Task-Relevant Source Data
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    Chapter 8 Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions
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    Chapter 9 Source-Free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition
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    Chapter 10 BMD: A General Class-Balanced Multicentric Dynamic Prototype Strategy for Source-Free Domain Adaptation
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    Chapter 11 Generalized Brain Image Synthesis with Transferable Convolutional Sparse Coding Networks
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    Chapter 12 Incomplete Multi-view Domain Adaptation via Channel Enhancement and Knowledge Transfer
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    Chapter 13 DistPro: Searching a Fast Knowledge Distillation Process via Meta Optimization
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    Chapter 14 ML-BPM: Multi-teacher Learning with Bidirectional Photometric Mixing for Open Compound Domain Adaptation in Semantic Segmentation
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    Chapter 15 PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks
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    Chapter 16 Personalized Education: Blind Knowledge Distillation
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    Chapter 17 Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space
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    Chapter 18 How Stable Are Transferability Metrics Evaluations?
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    Chapter 19 Attention Diversification for Domain Generalization
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    Chapter 21 An Efficient Spatio-Temporal Pyramid Transformer for Action Detection
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    Chapter 22 Human Trajectory Prediction via Neural Social Physics
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    Chapter 23 Towards Open Set Video Anomaly Detection
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    Chapter 24 EclipSE : Efficient Long-Range Video Retrieval Using Sight and Sound
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    Chapter 25 Joint-Modal Label Denoising for Weakly-Supervised Audio-Visual Video Parsing
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    Chapter 26 Less Than Few: Self-shot Video Instance Segmentation
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    Chapter 27 Adaptive Face Forgery Detection in Cross Domain
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    Chapter 28 Real-Time Online Video Detection with Temporal Smoothing Transformers
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    Chapter 29 Tall Former: Temporal Action Localization with a Long-Memory Transformer
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    Chapter 31 TL;DW? Summarizing Instructional Videos with Task Relevance and Cross-Modal Saliency
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    Chapter 32 Rethinking Learning Approaches for Long-Term Action Anticipation
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    Chapter 33 DualFormer: Local-Global Stratified Transformer for Efficient Video Recognition
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    Chapter 34 Hierarchical Feature Alignment Network for Unsupervised Video Object Segmentation
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    Chapter 35 PAC-Net: Highlight Your Video via History Preference Modeling
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    Chapter 36 How Severe Is Benchmark-Sensitivity in Video Self-supervised Learning?
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    Chapter 37 A Sliding Window Scheme for Online Temporal Action Localization
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    Chapter 38 ERA: Expert Retrieval and Assembly for Early Action Prediction
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    Chapter 39 Dual Perspective Network for Audio-Visual Event Localization
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    Chapter 40 NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition
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    Chapter 41 Video Activity Localisation with Uncertainties in Temporal Boundary
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    Chapter 42 Temporal Saliency Query Network for Efficient Video Recognition
Attention for Chapter 19: Attention Diversification for Domain Generalization
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Chapter title
Attention Diversification for Domain Generalization
Chapter number 19
Book title
Computer Vision – ECCV 2022
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-19830-4_19
Book ISBNs
978-3-03-119829-8, 978-3-03-119830-4
Authors

Meng, Rang, Li, Xianfeng, Chen, Weijie, Yang, Shicai, Song, Jie, Wang, Xinchao, Zhang, Lei, Song, Mingli, Xie, Di, Pu, Shiliang

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 24%
Student > Master 3 14%
Researcher 1 5%
Student > Bachelor 1 5%
Unknown 11 52%
Readers by discipline Count As %
Computer Science 8 38%
Engineering 1 5%
Unknown 12 57%