29 citations · 70 across the 14 of their papers we have counts for
5 papers · 1 filter
OVGaussian: Generalizable 3D Gaussian Segmentation with Open Vocabularies
Runnan Chen, Xiangyu Sun, Zhaoqing Wang +8
Open-vocabulary scene understanding using 3D Gaussian (3DGS) representations has garnered considerable attention. However, existing methods mostly lift knowledge from large 2D visi…
An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models
Jiahao Sun, Chunmei Qing, Xiang Xu +10
In the rapidly evolving field of autonomous driving, precise segmentation of LiDAR data is crucial for understanding complex 3D environments. Traditional approaches often rely on d…
OpenESS: Event-based Semantic Scene Understanding with Open Vocabularies
Lingdong Kong, Youquan Liu, Lai Xing Ng +2
Event-based semantic segmentation (ESS) is a fundamental yet challenging task for event camera sensing. The difficulties in interpreting and annotating event data limit its scalabi…
Multi-Space Alignments Towards Universal LiDAR Segmentation
Youquan Liu, Lingdong Kong, Xiaoyang Wu +5
A unified and versatile LiDAR segmentation model with strong robustness and generalizability is desirable for safe autonomous driving perception. This work presents M3Net, a one-of…
Visual Foundation Models Boost Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation
Jingyi Xu, Weidong Yang, Lingdong Kong +4
Unsupervised domain adaptation (UDA) is vital for alleviating the workload of labeling 3D point cloud data and mitigating the absence of labels when facing a newly defined domain.…