Expurgate
发表于 2025-3-23 12:16:09
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散开
发表于 2025-3-23 15:31:42
,Learning to Localize Actions in Instructional Videos with LLM-Based Multi-pathway Text-Video Alignmscale training videos. Recent works focus on learning the cross-modal alignment between video segments and ASR-transcripted narration texts through contrastive learning. However, these methods fail to account for the alignment noise, .., irrelevant narrations to the instructional task in videos and
屈尊
发表于 2025-3-23 21:46:13
,Improving Hyperbolic Representations via Gromov-Wasserstein Regularization,networks have been commonly applied for learning such representations from data, but they often fall short in preserving the geometric structures of the original feature spaces. In response to this challenge, our work applies the Gromov-Wasserstein (GW) distance as a novel regularization mechanism w
做作
发表于 2025-3-24 02:01:34
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BUMP
发表于 2025-3-24 05:00:22
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侵略者
发表于 2025-3-24 07:06:50
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粗鲁的人
发表于 2025-3-24 11:01:37
,Dense Hand-Object (HO) GraspNet with Full Grasping Taxonomy and Dynamics,of annotations. In this work, we present a comprehensive new training dataset for hand-object interaction called HOGraspNet. It is the only real dataset that captures full grasp taxonomies, providing grasp annotation and wide intraclass variations. Using grasp taxonomies as atomic actions, their spa
Mercantile
发表于 2025-3-24 18:47:21
,Human Pose Recognition via Occlusion-Preserving Abstract Images, is the dominant trend, stick-figures do not preserve occlusion information that is inherent in an image, resulting in significant ambiguities that are ruled out when occlusion information is present. In addition, datasets with ground truth 3D poses are much harder to obtain in contrast to similar h
BADGE
发表于 2025-3-24 21:37:28
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确定的事
发表于 2025-3-25 00:49:54
Conference proceedings 2025uter Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024...The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforceme