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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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樓主: frustrate
51#
發(fā)表于 2025-3-30 10:51:38 | 只看該作者
3D Shape Temporal Aggregation for?Video-Based Clothing-Change Person Re-identificationodule. It embeds the identity information into the generation of 3D shapes by the joint learning of shape estimation and identity recognition. Second, a difference-aware shape aggregation module is designed to measure inter-frame 3D human shape differences and automatically select the unique 3D shap
52#
發(fā)表于 2025-3-30 14:45:27 | 只看該作者
53#
發(fā)表于 2025-3-30 19:44:30 | 只看該作者
54#
發(fā)表于 2025-3-30 21:19:03 | 只看該作者
IoU-Enhanced Attention for?End-to-End Task Specific Object Detectionlassification and regression, we add two lightweight projection heads to provide the dynamic channel masks based on object query, and they multiply with the output from dynamic convs, making the results suitable for the two different tasks. We validate the proposed scheme on different datasets, incl
55#
發(fā)表于 2025-3-31 03:40:20 | 只看該作者
56#
發(fā)表于 2025-3-31 08:24:34 | 只看該作者
Cross-Architecture Knowledge Distillationeme is further presented to improve the robustness and stability of the framework. Extensive experiments show that the proposed method outperforms 14 state-of-the-arts on both small-scale and large-scale datasets.
57#
發(fā)表于 2025-3-31 11:57:55 | 只看該作者
Cross-Domain Local Characteristic Enhanced Deepfake Video Detection forgery-sensitive local regions of a human face to guide the model to enhance subtle artifacts and localize potential anomalies. Extensive experiments on several benchmark datasets demonstrate the impressive performance of our method, and we achieve superiority over several state-of-the-art methods
58#
發(fā)表于 2025-3-31 13:23:08 | 只看該作者
59#
發(fā)表于 2025-3-31 20:29:10 | 只看該作者
60#
發(fā)表于 2025-3-31 23:47:10 | 只看該作者
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