5 citations · 7 across the 5 of their papers we have counts for
5 papers
Robust Unsupervised Domain Adaptation for 3D Point Cloud Segmentation Under Source Adversarial Attacks
Haosheng Li, Junjie Chen, Yuecong Xu +1
Unsupervised domain adaptation (UDA) frameworks have shown good generalization capabilities for 3D point cloud semantic segmentation models on clean data. However, existing works o…
ProtoGuard-guided PROPEL: Class-Aware Prototype Enhancement and Progressive Labeling for Incremental 3D Point Cloud Segmentation
Haosheng Li, Yuecong Xu, Junjie Chen +1
3D point cloud semantic segmentation technology has been widely used. However, in real-world scenarios, the environment is evolving. Thus, offline-trained segmentation models may l…
Overlap-Aware Feature Learning for Robust Unsupervised Domain Adaptation for 3D Semantic Segmentation
Junjie Chen, Yuecong Xu, Haosheng Li +1
3D point cloud semantic segmentation (PCSS) is a cornerstone for environmental perception in robotic systems and autonomous driving, enabling precise scene understanding through po…
Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation
Ping Li, Junjie Chen, Li Yuan +2
To alleviate the expensive human labeling, semi-supervised semantic segmentation employs a few labeled images and an abundant of unlabeled images to predict the pixel-level label m…
Residual Spatial Fusion Network for RGB-Thermal Semantic Segmentation
Ping Li, Junjie Chen, Binbin Lin +1
Semantic segmentation plays an important role in widespread applications such as autonomous driving and robotic sensing. Traditional methods mostly use RGB images which are heavily…