most citedTransformation-Equivariant 3D Object Detection for Autonomous Driving

13 citations · 13 across the 4 of their papers we have counts for

collaborators

5 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.CV202213 cited

Transformation-Equivariant 3D Object Detection for Autonomous Driving

Hai Wu, Chenglu Wen, Wei Li +3

3D object detection received increasing attention in autonomous driving recently. Objects in 3D scenes are distributed with diverse orientations. Ordinary detectors do not explicit…