activity
20222026
most citedSurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving

10 citations · 51 across the 15 of their papers we have counts for

collaborators

16 papers

cs.CV2026

Vega: Learning to Drive with Natural Language Instructions

Sicheng Zuo, Yuxuan Li, Wenzhao Zheng +3

Vision-language-action models have reshaped autonomous driving to incorporate languages into the decision-making process. However, most existing pipelines only utilize the language…

cs.CV2025

Geometry-Aware Single-Image 4D Synthesis via Dense Trajectory Generation

Yanran Zhang, Ziyi Wang, Wenzhao Zheng +3

Generating interactive and dynamic 4D scenes from a single static image remains a core challenge. Most existing generate-then-reconstruct and reconstruct-then-generate methods deco…

cs.CV2025

OmniNWM: Omniscient Driving Navigation World Models

Bohan Li, Zhuang Ma, Dalong Du +10

Autonomous driving world models are expected to work effectively across three core dimensions: state, action, and reward. However, existing methods are typically restricted to frag…

cs.RO2025

R2RGEN: Real-to-Real 3D Data Generation for Spatially Generalized Manipulation

Xiuwei Xu, Angyuan Ma, Hankun Li +4

Towards the aim of generalized robotic manipulation, spatial generalization is the most fundamental capability that requires the policy to work robustly under different spatial dis…

cs.CV2023★ 8 cited

OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction

Yunpeng Zhang, Zheng Zhu, Dalong Du

The vision-based perception for autonomous driving has undergone a transformation from the bird-eye-view (BEV) representations to the 3D semantic occupancy. Compared with the BEV p…

cs.CV2023★ 6 cited

OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception

Xiaofeng Wang, Zheng Zhu, Wenbo Xu +7

Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant be…