Zobrazeno 1 - 10
of 243
pro vyhledávání: '"Li, Wanlong"'
Visual bird's eye view (BEV) semantic segmentation helps autonomous vehicles understand the surrounding environment only from images, including static elements (e.g., roads) and dynamic elements (e.g., vehicles, pedestrians). However, the high cost o
Externí odkaz:
http://arxiv.org/abs/2308.14525
The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised methods. To further improve the performance, recent works mainly focus on d
Externí odkaz:
http://arxiv.org/abs/2301.08414
Autor:
Zhao, Jianghui, Li, Wanlong, Shi, Yiling, Zheng, Xianhong, Feng, Quan, Low, Siew Chun, Tan, Soon Huat, Liu, Zhi
Publikováno v:
In Journal of Colloid And Interface Science 15 January 2025 678 Part B:1112-1124
Autor:
Yang, Xuemeng, Zou, Hao, Kong, Xin, Huang, Tianxin, Liu, Yong, Li, Wanlong, Wen, Feng, Zhang, Hongbo
Outdoor scene completion is a challenging issue in 3D scene understanding, which plays an important role in intelligent robotics and autonomous driving. Due to the sparsity of LiDAR acquisition, it is far more complex for 3D scene completion and sema
Externí odkaz:
http://arxiv.org/abs/2109.11453
LiDAR-based SLAM system is admittedly more accurate and stable than others, while its loop closure detection is still an open issue. With the development of 3D semantic segmentation for point cloud, semantic information can be obtained conveniently a
Externí odkaz:
http://arxiv.org/abs/2106.11516
Publikováno v:
In Separation and Purification Technology 19 February 2025 354 Part 5
This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant search space. A main challenge in 3D single object tracking is how to
Externí odkaz:
http://arxiv.org/abs/2010.11510
Autor:
Kong, Xin, Yang, Xuemeng, Zhai, Guangyao, Zhao, Xiangrui, Zeng, Xianfang, Wang, Mengmeng, Liu, Yong, Li, Wanlong, Wen, Feng
Due to the difficulty in generating the effective descriptors which are robust to occlusion and viewpoint changes, place recognition for 3D point cloud remains an open issue. Unlike most of the existing methods that focus on extracting local, global,
Externí odkaz:
http://arxiv.org/abs/2008.11459
Autor:
Liu, Xiaoyan, Cui, Yaoping, Li, Wanlong, Li, Mengdi, Li, Nan, Shi, Zhifang, Dong, Jinwei, Xiao, Xiangming
Publikováno v:
In Science of the Total Environment 25 November 2023 901
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.