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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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51#
發(fā)表于 2025-3-30 10:20:43 | 只看該作者
“Kosten” und Nutzen von Selbsthilfegruppena faster integer linear programming formulation, and the framework is flexible, supporting segmentations from individual off-the-shelf cell segmentation models or their combination as an ensemble. The code is available as supplementary material.
52#
發(fā)表于 2025-3-30 14:15:51 | 只看該作者
53#
發(fā)表于 2025-3-30 17:52:25 | 只看該作者
,Dienstleistungsvertrag für Wohnmakler,cally allocates computation resources in each sampling step to improve the generation efficiency of diffusion models. To assess the effects of changes in computational effort on image quality, we present a timestep-aware uncertainty estimation module (UEM). Integrated at each intermediate layer, the
54#
發(fā)表于 2025-3-30 20:49:10 | 只看該作者
55#
發(fā)表于 2025-3-31 02:01:24 | 只看該作者
56#
發(fā)表于 2025-3-31 05:57:50 | 只看該作者
Alexander Minnaert,Piet J. Janssenr model achieves state-of-the-art results in object insertion, particularly for in-the-wild images. We show compelling results on diverse insertion prompts and images across various domains. In addition, we automate iterative insertion by combining our insertion model with beam search guided by CLIP
57#
發(fā)表于 2025-3-31 09:22:13 | 只看該作者
Alexander Minnaert,Piet J. Janssentedly for each case. SuperFedNAS addresses these challenges by decoupling the training and search in federated NAS. SuperFedNAS co-trains a large number of diverse DNN architectures contained inside one supernet in the FL setting. Post-training, clients perform NAS locally to find specialized DNNs b
58#
發(fā)表于 2025-3-31 14:35:54 | 只看該作者
Nilotpal Borah,Abhijit Gogoi,Jiban SaikiaVL tasks: When region annotations are provided, CRG increases absolute accuracy by up to . on ViP-Bench, a collection of six diverse region-based tasks such as recognition, math, and object relationship reasoning. We also show CRG’s applicability to spatial reasoning, with . improvement on What’sUp,
59#
發(fā)表于 2025-3-31 19:27:07 | 只看該作者
Nilotpal Borah,Abhijit Gogoi,Jiban Saikiaons necessary for prompting. To bridge this gap and foster further research on this topic,?we introduce Occluded PoseTrack-ReID, a novel ReID dataset with keypoints labels, that features strong inter-person occlusions. Furthermore, we release custom keypoint labels for four popular ReID benchmarks.
60#
發(fā)表于 2025-3-31 22:06:39 | 只看該作者
Bipransh Kumar Tiwary,Kiran Pradhanand cross-attention to operate on the aggregated latent space. Extensive quantitative and qualitative experimental analysis, together with a user study, demonstrate that our method maintains compatibility with the input prompt and visual quality of the generated images while increasing their semanti
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