collaborators

9 papers

cs.CV2026

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.CV2026

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method

Bohan Li, Xin Jin, Hu Zhu +9

Driving scene generation is a critical domain for autonomous driving, enabling downstream applications, including perception and planning evaluation. Occupancy-centric methods have…

cs.CV2026

DriveCtrl: Conditioned Sim-to-Real Driving Video Generation

Haonan Zhao, Yiting Wang, Jingkun Chen +3

Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated data, the domain gap between s…

cs.CV2026

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation

Bohan Li, Shuojue Yang, Baorui Peng +10

Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dimensional control vectors must prec…

cs.CV2025

ORV: 4D Occupancy-centric Robot Video Generation

Xiuyu Yang, Bohan Li, Shaocong Xu +9

Recent embodied intelligence suffers from data scarcity, while conventional simulators lack visual realism. Controllable video generation is emerging as a promising data engine, ye…

cs.CV2025

Stability Under Scrutiny: Benchmarking Representation Paradigms for Online HD Mapping

Hao Shan, Ruikai Li, Han Jiang +8

As one of the fundamental modules in autonomous driving, online high-definition (HD) maps have attracted significant attention due to their cost-effectiveness and real-time capabil…