1 citations · 2 across the 4 of their papers we have counts for
5 papers · 1 filter
OPUS-V2: Bridging the Gap between Sparse Points and Dense Voxels
Jiabao Wang, Qiang Meng, Liujiang Yan +3
The point-based occupancy prediction paradigm has achieved an attractive trade-off between accuracy and efficiency by modeling 3D space sparsely. However, its predictions inherentl…
OPUS: Occupancy Prediction Using a Sparse Set
Jiabao Wang, Zhaojiang Liu, Qiang Meng +6
Occupancy prediction, aiming at predicting the occupancy status within voxelized 3D environment, is quickly gaining momentum within the autonomous driving community. Mainstream occ…
Towards Stable 3D Object Detection
Jiabao Wang, Qiang Meng, Guochao Liu +4
In autonomous driving, the temporal stability of 3D object detection greatly impacts the driving safety. However, the detection stability cannot be accessed by existing metrics suc…
Small, Versatile and Mighty: A Range-View Perception Framework
Qiang Meng, Xiao Wang, JiaBao Wang +2
Despite its compactness and information integrity, the range view representation of LiDAR data rarely occurs as the first choice for 3D perception tasks. In this work, we further p…
Curricular Object Manipulation in LiDAR-based Object Detection
Ziyue Zhu, Qiang Meng, Xiao Wang +3
This paper explores the potential of curriculum learning in LiDAR-based 3D object detection by proposing a curricular object manipulation (COM) framework. The framework embeds the…