5 papers · 1 filter
RAHF-Net: Range-Aware Heterogeneous Fusion for LiDAR-Assisted RGB Semantic Segmentation
R. D. Lin, Pengcheng Weng, Ge Wang +2
This paper studies LiDAR-assisted RGB semantic segmentation, where LiDAR point-cloud features improve dense pixel-wise predictions in the RGB image plane rather than 3D point label…
Purify-then-Align: Towards Robust Human Sensing under Modality Missing with Knowledge Distillation from Noisy Multimodal Teacher
Pengcheng Weng, Yanyu Qian, Yangxin Xu +1
Robust multimodal human sensing must overcome the critical challenge of missing modalities. Two principal barriers are the Representation Gap between heterogeneous data and the Con…
COMPASS: Fusion-Matched Supervision for Missing-Modality Human Sensing
Hao Wang, Yanyu Qian, Pengcheng Weng +4
Multimodal human activity recognition (HAR) and human pose estimation (HPE) must cope with modalities missing at inference. Completions generated for a fixed fusion model must pres…
Diverse via bounded Agreement: Geometric Regularization for Multimodal Fusion
Zixuan Xia, Hao Wang, Pengcheng Weng +4
Multimodal fusion is often treated as an optimization-balancing problem, where training signals are adjusted to prevent one modality from dominating the others. However, balanced o…
HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving
R. D. Lin, Pengcheng Weng, Yinqiao Wang +3
LiDAR point cloud semantic segmentation plays a crucial role in autonomous driving. In recent years, semi-supervised methods have gained popularity due to their significant reducti…