collaborators

6 papers

cs.CV2025

QuadricFormer: Scene as Superquadrics for 3D Semantic Occupancy Prediction

Sicheng Zuo, Wenzhao Zheng, Xiaoyong Han +3

3D occupancy prediction is crucial for robust autonomous driving systems as it enables comprehensive perception of environmental structures and semantics. Most existing methods emp…

cs.CV2024

GaussianWorld: Gaussian World Model for Streaming 3D Occupancy Prediction

Sicheng Zuo, Wenzhao Zheng, Yuanhui Huang +2

3D occupancy prediction is important for autonomous driving due to its comprehensive perception of the surroundings. To incorporate sequential inputs, most existing methods fuse re…

cs.CV2024

GaussianAD: Gaussian-Centric End-to-End Autonomous Driving

Wenzhao Zheng, Junjie Wu, Yao Zheng +8

Vision-based autonomous driving shows great potential due to its satisfactory performance and low costs. Most existing methods adopt dense representations (e.g., bird's eye view) o…

cs.CV2024

Doe-1: Closed-Loop Autonomous Driving with Large World Model

Wenzhao Zheng, Zetian Xia, Yuanhui Huang +3

End-to-end autonomous driving has received increasing attention due to its potential to learn from large amounts of data. However, most existing methods are still open-loop and suf…

cs.CV2024

GPD-1: Generative Pre-training for Driving

Zixun Xie, Sicheng Zuo, Wenzhao Zheng +5

Modeling the evolutions of driving scenarios is important for the evaluation and decision-making of autonomous driving systems. Most existing methods focus on one aspect of scene e…

cs.CV2024

EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene Understanding

Yuqi Wu, Wenzhao Zheng, Sicheng Zuo +3

3D occupancy prediction provides a comprehensive description of the surrounding scenes and has become an essential task for 3D perception. Most existing methods focus on offline pe…