activity
20222026
most citedDeep Height Decoupling for Precise Vision-based 3D Occupancy Prediction

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Levy-Driven Correspondence Estimation for Registration

Qianliang Wu, Jiaqi Yang, Wankou Yang +4

Finding reliable point correspondences is difficult when point clouds have low overlap or undergo non-rigid deformation. Iterative refinement can correct uncertain matches, but cos…

cs.CV2026

LiAuto-GeoX: Efficient Grounded Driving Transformer

Jiawei Lian, Haoyi Sun, Yang Wu +8

Dense 3D reconstruction has demonstrated immense potential for spatial understanding, yet its viability as a real-time, onboard representation for autonomous driving remains an ope…

cs.CV2025

Sketchy Bounding-box Supervision for 3D Instance Segmentation

Qian Deng, Le Hui, Jin Xie +1

Bounding box supervision has gained considerable attention in weakly supervised 3D instance segmentation. While this approach alleviates the need for extensive point-level annotati…

cs.CV2025

AuxDet: Auxiliary Metadata Matters for Omni-Domain Infrared Small Target Detection

Yangting Shi, Yinfei Zhu, Renjie He +4

Omni-domain infrared small target detection (Omni-IRSTD) poses formidable challenges, as a single model must seamlessly adapt to diverse imaging systems, varying resolutions, and m…

cs.CV2025

Learning Class Prototypes for Unified Sparse Supervised 3D Object Detection

Yun Zhu, Le Hui, Hang Yang +3

Both indoor and outdoor scene perceptions are essential for embodied intelligence. However, current sparse supervised 3D object detection methods focus solely on outdoor scenes wit…

cs.CV2024★ 1 cited

Deep Height Decoupling for Precise Vision-based 3D Occupancy Prediction

Yuan Wu, Zhiqiang Yan, Zhengxue Wang +3

The task of vision-based 3D occupancy prediction aims to reconstruct 3D geometry and estimate its semantic classes from 2D color images, where the 2D-to-3D view transformation is a…

cs.CV2022

Point Cloud Registration-Driven Robust Feature Matching for 3D Siamese Object Tracking

Haobo Jiang, Kaihao Lan, Le Hui +3

Learning robust feature matching between the template and search area is crucial for 3D Siamese tracking. The core of Siamese feature matching is how to assign high feature similar…