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pro vyhledávání: '"Shan Jiayao"'
3D single object tracking is a key task in 3D computer vision. However, the sparsity of point clouds makes it difficult to compute the similarity and locate the object, posing big challenges to the 3D tracker. Previous works tried to solve the proble
Externí odkaz:
http://arxiv.org/abs/2210.00519
LiDAR-based 3D single object tracking is a challenging issue in robotics and autonomous driving. Currently, existing approaches usually suffer from the problem that objects at long distance often have very sparse or partially-occluded point clouds, w
Externí odkaz:
http://arxiv.org/abs/2209.00860
Feature fusion and similarity computation are two core problems in 3D object tracking, especially for object tracking using sparse and disordered point clouds. Feature fusion could make similarity computing more efficient by including target object i
Externí odkaz:
http://arxiv.org/abs/2110.14921
Publikováno v:
In Journal of the Taiwan Institute of Chemical Engineers August 2024 161
3D single object tracking is a key issue for robotics. In this paper, we propose a transformer module called Point-Track-Transformer (PTT) for point cloud-based 3D single object tracking. PTT module contains three blocks for feature embedding, positi
Externí odkaz:
http://arxiv.org/abs/2108.06455
Autor:
Zeng, Qinghua, Zhu, Dawei, Shan, Jiayao, Gao, Qingwei, Xu, Jinting, Xu, Qunjie, Shi, PengHui, Min, YuLin
Publikováno v:
In Chemical Engineering Journal 15 April 2024 486
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LiDAR-based 3D single object tracking is a challenging issue in robotics and autonomous driving. Currently, existing approaches usually suffer from the problem that objects at long distance often have very sparse or partially-occluded point clouds, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c1b5567f27dd2fcaf0089b83f87e659