2 citations · 3 across the 10 of their papers we have counts for
5 papers · 2 filters
PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentation
Shoumeng Qiu, Xinrun Li, XiangYang Xue +1
Although multiview fusion has demonstrated potential in LiDAR segmentation, its dependence on computationally intensive point-based interactions, arising from the lack of fixed cor…
Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic Segmentation
Shoumeng Qiu, Jie Chen, Xinrun Li +3
In this paper, we introduce a novel knowledge distillation approach for the semantic segmentation task. Unlike previous methods that rely on power-trained teachers or other modalit…
Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs
Rong Ma, Jie Chen, Xiangyang Xue +1
Deep supervised models possess significant capability to assimilate extensive training data, thereby presenting an opportunity to enhance model performance through training on mult…
Towards Camera Open-set 3D Object Detection for Autonomous Driving Scenarios
Zhuolin He, Xinrun Li, Jiacheng Tang +4
Conventional camera-based 3D object detectors in autonomous driving are limited to recognizing a predefined set of objects, which poses a safety risk when encountering novel or uns…
FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View
Jiawei Hou, Xiaoyan Li, Wenhao Guan +5
In autonomous driving, 3D occupancy prediction outputs voxel-wise status and semantic labels for more comprehensive understandings of 3D scenes compared with traditional perception…