19 citations · 20 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
Guo Chen, Yifei Huang, Jilan Xu +7
Understanding videos is one of the fundamental directions in computer vision research, with extensive efforts dedicated to exploring various architectures such as RNN, 3D CNN, and…
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…
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…