23 citations · 53 across the 69 of their papers we have counts for
11 papers · 2 filters
StreetCrafter: Street View Synthesis with Controllable Video Diffusion Models
Yunzhi Yan, Zhen Xu, Haotong Lin +8
This paper aims to tackle the problem of photorealistic view synthesis from vehicle sensor data. Recent advancements in neural scene representation have achieved notable success in…
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…
DiVE: DiT-based Video Generation with Enhanced Control
Junpeng Jiang, Gangyi Hong, Lijun Zhou +10
Generating high-fidelity, temporally consistent videos in autonomous driving scenarios faces a significant challenge, e.g. problematic maneuvers in corner cases. Despite recent vid…
Autonomous LLM-Enhanced Adversarial Attack for Text-to-Motion
Honglei Miao, Fan Ma, Ruijie Quan +2
Human motion generation driven by deep generative models has enabled compelling applications, but the ability of text-to-motion (T2M) models to produce realistic motions from text…
Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation
Enhui Ma, Lijun Zhou, Tao Tang +9
Using generative models to synthesize new data has become a de-facto standard in autonomous driving to address the data scarcity issue. Though existing approaches are able to boost…
3DRealCar: An In-the-wild RGB-D Car Dataset with 360-degree Views
Xiaobiao Du, Yida Wang, Haiyang Sun +8
3D cars are commonly used in self-driving systems, virtual/augmented reality, and games. However, existing 3D car datasets are either synthetic or low-quality, limiting their appli…