collaborators
Showing cs.CVShow all

17 papers · 1 filter

cs.CV2026

DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Driving

Qimao Chen, Fang Li, Yuechen Luo +11

Reward models play a pivotal role in reinforcement learning (RL) and multi-modal trajectory selection for autonomous driving. However, acquiring such rewards typically relies on ha…

cs.CV2026

CP4D: Compositional Physics-aware 4D Scene Generation

Hanxin Zhu, Cong Wang, Tianyu He +4

4D generation (\textit{i.e.}, dynamic 3D generation) has recently emerged as a rapidly growing research frontier due to its powerful spatiotemporal modeling capabilities. However,…

cs.CV2026

DVGT: Driving Visual Geometry Transformer

Sicheng Zuo, Zixun Xie, Wenzhao Zheng +6

Perceiving and reconstructing 3D scene geometry from visual inputs is crucial for autonomous driving. However, there still lacks a driving-targeted dense geometry perception model…

cs.CV2026

AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture-of-Transformers for End-to-End Autonomous Driving

Wenhui Huang, Songyan Zhang, Qihang Huang +6

Integrating vision-language models (VLMs) into end-to-end (E2E) autonomous driving (AD) systems has shown promise in improving scene understanding. However, existing integration st…

cs.CV2026

Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation

Jinghui Lu, Jiayi Guan, Zhijian Huang +47

Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature imposes a latency cost that is…

cs.CV2026

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale

Sicheng Zuo, Zixun Xie, Wenzhao Zheng +6

End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models, which focus on learning language descr…