8 papers
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…
Seg2Box: 3D Object Detection by Point-Wise Semantics Supervision
Maoji Zheng, Ziyu Xu, Qiming Xia +3
LiDAR-based 3D object detection and semantic segmentation are critical tasks in 3D scene understanding. Traditional detection and segmentation methods supervise their models throug…
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…
SP3D: Boosting Sparsely-Supervised 3D Object Detection via Accurate Cross-Modal Semantic Prompts
Shijia Zhao, Qiming Xia, Xusheng Guo +5
Recently, sparsely-supervised 3D object detection has gained great attention, achieving performance close to fully-supervised 3D objectors while requiring only a few annotated inst…