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Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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發(fā)表于 2025-3-23 13:16:24 | 只看該作者
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發(fā)表于 2025-3-23 23:09:19 | 只看該作者
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發(fā)表于 2025-3-24 04:55:42 | 只看該作者
Diverse Human Motion Prediction Guided by Multi-level Spatial-Temporal Anchors,s the multi-modal nature of human motions primarily through likelihood-based sampling, where the mode collapse has been widely observed. In this paper, we propose a simple yet effective approach that disentangles randomly sampled codes with a . to promote sample precision and diversity. Anchors are
16#
發(fā)表于 2025-3-24 06:40:45 | 只看該作者
,Learning Pedestrian Group Representations for?Multi-modal Trajectory Prediction, prediction define a particular set of individual actions to implicitly model group actions. In this paper, we present a novel architecture named GP-Graph which has collective group representations for effective pedestrian trajectory prediction in crowded environments, and is compatible with all typ
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發(fā)表于 2025-3-24 11:35:05 | 只看該作者
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發(fā)表于 2025-3-24 18:41:16 | 只看該作者
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發(fā)表于 2025-3-24 22:19:40 | 只看該作者
,Point Cloud Compression with?Range Image-Based Entropy Model for?Autonomous Driving,r large volume. In this paper, we propose a range image-based three-stage framework to compress the scanning LiDAR’s point clouds using the entropy model. In our three-stage framework, we refine the coarser range image by converting the regression problem into the limited classification problem to i
20#
發(fā)表于 2025-3-24 23:51:29 | 只看該作者
Conference proceedings 2022ning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..
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