5 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…
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…
OWL: Unsupervised 3D Object Detection by Occupancy Guided Warm-up and Large Model Priors Reasoning
Xusheng Guo, Wanfa Zhang, Shijia Zhao +5
Unsupervised 3D object detection leverages heuristic algorithms to discover potential objects, offering a promising route to reduce annotation costs in autonomous driving. Existing…
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…
WinMamba: Multi-Scale Shifted Windows in State Space Model for 3D Object Detection
Longhui Zheng, Qiming Xia, Xiaolu Chen +2
3D object detection is critical for autonomous driving, yet it remains fundamentally challenging to simultaneously maximize computational efficiency and capture long-range spatial…