collaborators

6 papers

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

SC3D: Label-Efficient Outdoor 3D Object Detection via Single Click Annotation

Qiming Xia, Hongwei Lin, Wei Ye +4

LiDAR-based outdoor 3D object detection has received widespread attention. However, training 3D detectors from the LiDAR point cloud typically relies on expensive bounding box anno…