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20212025
most cited3D-SiamRPN: An End-to-End Learning Method for Real-Time 3D Single Object Tracking Using Raw Point Cloud

89 citations · 132 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

Towards 3D Object-Centric Feature Learning for Semantic Scene Completion

Weihua Wang, Yubo Cui, Xiangru Lin +2

Vision-based 3D Semantic Scene Completion (SSC) has received growing attention due to its potential in autonomous driving. While most existing approaches follow an ego-centric para…

cs.CV20251 cited

4D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic Segmentation

Jiexi Zhong, Zhiheng Li, Yubo Cui +1

Semantic segmentation of LiDAR points has significant value for autonomous driving and mobile robot systems. Most approaches explore spatio-temporal information of multi-scan to id…

cs.CV2024

LOMA: Language-assisted Semantic Occupancy Network via Triplane Mamba

Yubo Cui, Zhiheng Li, Jiaqiang Wang +1

Vision-based 3D occupancy prediction has become a popular research task due to its versatility and affordability. Nowadays, conventional methods usually project the image-based vis…

cs.CV2022

Exploiting More Information in Sparse Point Cloud for 3D Single Object Tracking

Yubo Cui, Jiayao Shan, Zuoxu Gu +2

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…

cs.CV202132 cited

3D Object Tracking with Transformer

Yubo Cui, Zheng Fang, Jiayao Shan +2

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…

cs.CV202189 cited

3D-SiamRPN: An End-to-End Learning Method for Real-Time 3D Single Object Tracking Using Raw Point Cloud

Zheng Fang, Sifan Zhou, Yubo Cui +1

3D single object tracking is a key issue for autonomous following robot, where the robot should robustly track and accurately localize the target for efficient following. In this p…