April 25, 2024, 7:46 p.m. | Kuan-Chih Huang, Weijie Lyu, Ming-Hsuan Yang, Yi-Hsuan Tsai

cs.CV updates on arXiv.org arxiv.org

arXiv:2312.08371v2 Announce Type: replace
Abstract: Recent temporal LiDAR-based 3D object detectors achieve promising performance based on the two-stage proposal-based approach. They generate 3D box candidates from the first-stage dense detector, followed by different temporal aggregation methods. However, these approaches require per-frame objects or whole point clouds, posing challenges related to memory bank utilization. Moreover, point clouds and trajectory features are combined solely based on concatenation, which may neglect effective interactions between them. In this paper, we propose a point-trajectory transformer …

3d object 3d object detection arxiv cs.cv detection object temporal trajectory transformer type

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