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Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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樓主: hormone-therapy
51#
發(fā)表于 2025-3-30 11:59:29 | 只看該作者
https://doi.org/10.1007/3-540-28527-Xtilizes cycle consistency as weak supervision to align discriminative temporal clips or spatial patches. Our model achieves state-of-the-art performance on four benchmarks especially under the most challenging 1-shot recognition setting.
52#
發(fā)表于 2025-3-30 14:04:15 | 只看該作者
53#
發(fā)表于 2025-3-30 19:26:32 | 只看該作者
54#
發(fā)表于 2025-3-31 00:05:46 | 只看該作者
Target-Absent Human Attention, that produces an in-network feature pyramid, all with minimal computational overhead. Our method integrates FFMs as the state representation in inverse reinforcement learning. Experimentally, we improve the state of the art in predicting human target-absent search behavior on the COCO-Search18 data
55#
發(fā)表于 2025-3-31 02:09:36 | 只看該作者
,Iwin: Human-Object Interaction Detection via?Transformer with?Irregular Windows,I detection benchmark datasets, HICO-DET and V-COCO. Results show our method outperforms existing Transformers-based methods by large margins (3.7 mAP gain on HICO-DET and 2.0 mAP gain on V-COCO) with fewer training epochs (.).
56#
發(fā)表于 2025-3-31 06:08:35 | 只看該作者
57#
發(fā)表于 2025-3-31 09:35:29 | 只看該作者
58#
發(fā)表于 2025-3-31 13:28:02 | 只看該作者
,Collaborating Domain-Shared and?Target-Specific Feature Clustering for?Cross-domain 3D Action Recogo label generation and feature clustering. Furthermore, to leverage the complementarity of domain-shared features and target-specific features, we propose a novel collaborative clustering strategy to enforce pair-wise relationship consistency between the two branches. We conduct extensive experiment
59#
發(fā)表于 2025-3-31 18:59:25 | 只看該作者
Is Appearance Free Action Recognition Possible?, its related RGB video. Our results show a notable decrease in performance for all architectures on AFD compared to RGB. We also conducted a complimentary study with humans that shows their recognition accuracy on AFD and RGB is very similar and much better than the evaluated architectures on AFD. O
60#
發(fā)表于 2025-3-31 21:43:28 | 只看該作者
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