15 papers · 1 filter
SRUG: Shadow-Guided Relightable Urban Scene with Generation Model
Yonghao Zhao, Zexin Yin, Jian Yang +2
Creating relightable urban scenes from images or videos is widely useful but highly ill-posed. Urban environments are typically unbounded and extend beyond the visible regions. As…
Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving
Yang Wu, Qiang Meng, Zhaojiang Liu +3
Current end-to-end autonomous driving models are fundamentally constrained by the behavioral cloning ceiling of imitation learning. While reinforcement learning offers a path to sm…
EponaV2: Driving World Model with Comprehensive Future Reasoning
Jiawei Xu, Zhizhou Zhong, Zhijian Shu +8
Data scaling plays a pivotal role in the pursuit of general intelligence. However, the prevailing perception-planning paradigm in autonomous driving relies heavily on expensive man…
3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image
Ze-Xin Yin, Liu Liu, Xinjie Wang +4
Compositional 3D scene generation from a single view requires the simultaneous recovery of scene layout and 3D assets. Existing approaches mainly fall into two categories: feed-for…
WorldSplat: Gaussian-Centric Feed-Forward 4D Scene Generation for Autonomous Driving
Ziyue Zhu, Zhanqian Wu, Zhenxin Zhu +8
Recent advances in driving-scene generation and reconstruction have demonstrated significant potential for enhancing autonomous driving systems by producing scalable and controllab…
MonoSE(3)-Diffusion: A Monocular SE(3) Diffusion Framework for Robust Camera-to-Robot Pose Estimation
Kangjian Zhu, Haobo Jiang, Yigong Zhang +3
We propose MonoSE(3)-Diffusion, a monocular SE(3) diffusion framework that formulates markerless, image-based robot pose estimation as a conditional denoising diffusion process. Th…