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cs.CV2025

CoGen: 3D Consistent Video Generation via Adaptive Conditioning for Autonomous Driving

Yishen Ji, Ziyue Zhu, Zhenxin Zhu +7

Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretra…

cs.CV2024

ImagineMap: Enhanced HD Map Construction with SD Maps

Yishen Ji, Zhiqi Li, Tong Lu

Track Mapless demands models to process multi-view images and Standard-Definition (SD) maps, outputting lane and traffic element perceptions along with their topological relationsh…

cs.CV2024

Driving with InternVL: Oustanding Champion in the Track on Driving with Language of the Autonomous Grand Challenge at CVPR 2024

Jiahan Li, Zhiqi Li, Tong Lu

This technical report describes the methods we employed for the Driving with Language track of the CVPR 2024 Autonomous Grand Challenge. We utilized a powerful open-source multimod…

cs.CV2024

Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?

Zhiqi Li, Zhiding Yu, Shiyi Lan +4

End-to-end autonomous driving recently emerged as a promising research direction to target autonomy from a full-stack perspective. Along this line, many of the latest works follow…

cs.CV2024

Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes

Diandian Guo, Deng-Ping Fan, Tongyu Lu +2

The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation (VSS) for driving scenes. Prio…