Titlebook: Computer Vision – ACCV 2022; 16th Asian Conferenc Lei Wang,Juergen Gall,Rama Chellappa Conference proceedings 2023 The Editor(s) (if applic

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书目名称Computer Vision – ACCV 2022影响因子(影响力)




书目名称Computer Vision – ACCV 2022影响因子(影响力)学科排名




书目名称Computer Vision – ACCV 2022网络公开度




书目名称Computer Vision – ACCV 2022网络公开度学科排名




书目名称Computer Vision – ACCV 2022被引频次




书目名称Computer Vision – ACCV 2022被引频次学科排名




书目名称Computer Vision – ACCV 2022年度引用




书目名称Computer Vision – ACCV 2022年度引用学科排名




书目名称Computer Vision – ACCV 2022读者反馈




书目名称Computer Vision – ACCV 2022读者反馈学科排名

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Exposing Face Forgery Clues via Retinex-Based Image Enhancementthe RGB feature extractor to concentrate more on forgery traces from an MSR perspective. The feature re-weighted interaction module implicitly learns the correlation between the two complementary modalities to promote feature learning for each other. Comprehensive experiments on several benchmarks s

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Occluded Facial Expression Recognition Using Self-supervised Learningownstream task. The experimental results on several databases containing both synthesized and realistic occluded facial images demonstrate the superiority of the proposed method over state-of-the-art methods.

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Focal and Global Spatial-Temporal Transformer for Skeleton-Based Action Recognitionteractions between the focal joints and body parts are incorporated to enhance the spatial dependencies via mutual cross-attention. (2) FG-TFormer: focal and global temporal transformer. Dilated temporal convolution is integrated into the global self-attention mechanism to explicitly capture the loc

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Spatial-Temporal Adaptive Graph Convolutional Network for Skeleton-Based Action Recognitioning the direct long-range temporal dependencies adaptively. On three large-scale skeleton action recognition datasets: NTU RGB+D 60, NTU RGB+D 120, and Kinetics Skeleton, the STA-GCN outperforms the existing state-of-the-art methods. The code is available at ..

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