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Titlebook: Computer Vision – ECCV 2024; 18th European Confer Ale? Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

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發(fā)表于 2025-3-23 13:16:31 | 只看該作者
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發(fā)表于 2025-3-23 23:17:59 | 只看該作者
Moulay Alaoui-Jamali,Rongyao ZhouPES to constrain the inter-class relative position of the substitute model in different directions. In this way, the substitute model is more consistent with the target model in the decision space, so that the generated adversarial samples will be more successful in misleading the target model to cl
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發(fā)表于 2025-3-24 02:52:42 | 只看該作者
Moulay Alaoui-Jamali,Rongyao Zhou. The first two modules can better initialize queries for line detection, while the last one refines predicted line instances. InsMapper is highly adaptable and can be seamlessly modified to align with the most recent HD map detection frameworks. Extensive experimental evaluations are conducted on t
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發(fā)表于 2025-3-24 08:54:34 | 只看該作者
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發(fā)表于 2025-3-24 21:12:48 | 只看該作者
,Federated Learning with?Local Openset Noisy Labels,s the problems, we design a label communication mechanism that shares “contrastive labels” randomly selected from clients with the server. The privacy of the shared contrastive labels is protected by label differential privacy (DP). Both the DP guarantee and the effectiveness of our approach are the
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發(fā)表于 2025-3-25 01:42:26 | 只看該作者
,Diff3DETR: Agent-Based Diffusion Model for?Semi-supervised 3D Object Detection,and the long-range attention in the transformer decoder to refine bounding boxes incrementally. Extensive experiments on ScanNet and SUN RGB-D datasets demonstrate that Diff3DETR outperforms state-of-the-art semi-supervised 3D object detection methods.
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