3 papers
cs.CV2026
ROVR-Open-Dataset: A Large-Scale Depth Dataset for Autonomous Driving
Xianda Guo, Ruijun Zhang, Yiqun Duan +9
Depth estimation is a fundamental component of spatial perception for autonomous driving and other unmanned systems operating in open urban environments. Existing depth datasets su…
cs.CV2025
ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving
Yongkang Li, Kaixin Xiong, Xiangyu Guo +12
Recent studies have explored leveraging the world knowledge and cognitive capabilities of Vision-Language Models (VLMs) to address the long-tail problem in end-to-end autonomous dr…
cs.CV2025
Genesis: Multimodal Driving Scene Generation with Spatio-Temporal and Cross-Modal Consistency
Xiangyu Guo, Zhanqian Wu, Kaixin Xiong +10
We present Genesis, a unified framework for joint generation of multi-view driving videos and LiDAR sequences with spatio-temporal and cross-modal consistency. Genesis employs a tw…