6 papers
MoniRefer: A Real-world Large-scale Multi-modal Dataset based on Roadside Infrastructure for 3D Visual Grounding
Panquan Yang, Junfei Huang, Zongzhangbao Yin +9
3D visual grounding aims to localize the object in 3D point cloud scenes that semantically corresponds to given natural language sentences. It is very critical for roadside infrast…
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…
AdaCo: Overcoming Visual Foundation Model Noise in 3D Semantic Segmentation via Adaptive Label Correction
Pufan Zou, Shijia Zhao, Weijie Huang +4
Recently, Visual Foundation Models (VFMs) have shown a remarkable generalization performance in 3D perception tasks. However, their effectiveness in large-scale outdoor datasets re…
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…