2 citations · 6 across the 8 of their papers we have counts for
9 papers
C2E: Boosting Ego-Only 3D Object Detection via Multi-Teacher Contrastive Knowledge Distillation
Jinlong Wang, Xun Huang, Qiming Xia +2
LiDAR-based 3D object detection is essential for autonomous driving systems. However, traditional Ego-only Perception (Eo-Perception) suffers from limited perspective and occlusion…
AW-MoE: All-Weather Mixture of Experts for Robust Multi-Modal 3D Object Detection
Hongwei Lin, Xun Huang, Chenglu Wen +1
Robust 3D object detection under adverse weather conditions is crucial for autonomous driving. However, most existing methods simply combine all weather samples for training while…
V2VLoc: Robust GNSS-Free Collaborative Perception via LiDAR Localization
Wenkai Lin, Qiming Xia, Wen Li +2
Multi-agents rely on accurate poses to share and align observations, enabling a collaborative perception of the environment. However, traditional GNSS-based localization often fail…
MSGNav: Unleashing the Power of Multi-modal 3D Scene Graph for Zero-Shot Embodied Navigation
Xun Huang, Shijia Zhao, Yunxiang Wang +6
Embodied navigation is a fundamental capability for robotic agents operating. Real-world deployment requires open vocabulary generalization and low training overhead, motivating ze…
Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual Labels
Qiming Xia, Wenkai Lin, Haoen Xiang +5
Unsupervised 3D object detection serves as an important solution for offline 3D object annotation. However, due to the data sparsity and limited views, the clustering-based label f…
V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detection
Xun Huang, Jinlong Wang, Qiming Xia +5
Current Vehicle-to-Everything (V2X) systems have significantly enhanced 3D object detection using LiDAR and camera data. However, these methods suffer from performance degradation…
L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection
Xun Huang, Ziyu Xu, Hai Wu +7
LiDAR-based vision systems are integral for 3D object detection, which is crucial for autonomous navigation. However, they suffer from performance degradation in adverse weather co…
Commonsense Prototype for Outdoor Unsupervised 3D Object Detection
Hai Wu, Shijia Zhao, Xun Huang +3
The prevalent approaches of unsupervised 3D object detection follow cluster-based pseudo-label generation and iterative self-training processes. However, the challenge arises due t…
Sunshine to Rainstorm: Cross-Weather Knowledge Distillation for Robust 3D Object Detection
Xun Huang, Hai Wu, Xin Li +3
LiDAR-based 3D object detection models have traditionally struggled under rainy conditions due to the degraded and noisy scanning signals. Previous research has attempted to addres…