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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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41#
發(fā)表于 2025-3-28 16:26:57 | 只看該作者
,Contrastive Region Guidance: Improving Grounding in?Vision-Language Models Without Training,VL 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,
42#
發(fā)表于 2025-3-28 22:20:46 | 只看該作者
Keypoint Promptable Re-Identification,ons 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.
43#
發(fā)表于 2025-3-29 02:46:03 | 只看該作者
44#
發(fā)表于 2025-3-29 05:19:43 | 只看該作者
45#
發(fā)表于 2025-3-29 11:04:00 | 只看該作者
,Animal Avatars: Reconstructing Animatable 3D Animals from?Casual Videos,etric compatibility with the input video frames. On the challenging CoP3D and APTv2 datasets, we demonstrate superior results (both in terms of pose estimates and predicted appearance) over existing template-free (RAC) and template-based approaches (BARC, BITE). Video results and additional informat
46#
發(fā)表于 2025-3-29 11:35:28 | 只看該作者
47#
發(fā)表于 2025-3-29 19:07:16 | 只看該作者
48#
發(fā)表于 2025-3-29 22:43:12 | 只看該作者
49#
發(fā)表于 2025-3-30 01:40:05 | 只看該作者
Alternativen zur Erwerbsarbeit?than previously reported. We also demonstrate a size-bias: small objects are often more easily attacked, even if the large objects are robust, a phenomenon not revealed by current evaluation metrics. Our results also demonstrate?that a diverse set of strong attacks is necessary, because different mo
50#
發(fā)表于 2025-3-30 06:11:19 | 只看該作者
Informelle ?konomie in Grossbritannienpoint conditions (height and pitch), weather and time of day, and (4) incorporating additional sensor modalities (depth) can improve aerial scene understanding. Our dataset and associated generation code are publicly available at:
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