4 citations · 5 across the 23 of their papers we have counts for
5 papers · 1 filter
ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration
Chaojun Ni, Guosheng Zhao, Xiaofeng Wang +13
Closed-loop simulation is crucial for end-to-end autonomous driving. Existing sensor simulation methods (e.g., NeRF and 3DGS) reconstruct driving scenes based on conditions that cl…
DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation
Guosheng Zhao, Chaojun Ni, Xiaofeng Wang +9
Closed-loop simulation is essential for advancing end-to-end autonomous driving systems. Contemporary sensor simulation methods, such as NeRF and 3DGS, rely predominantly on condit…
EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation
Xiaofeng Wang, Kang Zhao, Feng Liu +6
Video generation has emerged as a promising tool for world simulation, leveraging visual data to replicate real-world environments. Within this context, egocentric video generation…
DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation
Guosheng Zhao, Xiaofeng Wang, Zheng Zhu +4
World models have demonstrated superiority in autonomous driving, particularly in the generation of multi-view driving videos. However, significant challenges still exist in genera…
CoReS: Orchestrating the Dance of Reasoning and Segmentation
Xiaoyi Bao, Siyang Sun, Shuailei Ma +5
The reasoning segmentation task, which demands a nuanced comprehension of intricate queries to accurately pinpoint object regions, is attracting increasing attention. However, Mult…