1 citations · 1 across the 15 of their papers we have counts for
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DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model
Jingke Wang, Zhenru Zhao, Shuangming Lei +8
Vision-Language-Action driving models convert a pretrained Vision-Language Model into a driving policy, allowing them to use world knowledge and follow language guidances. However,…
SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation
Ruoyu Wang, Jingke Wang, Yukai Ma +5
Recently, world models have made significant progress in enhancing end-to-end driving systems through both future situation forecasting and improved scene understanding. However, e…
VEOcc: Voxel-Centric Online Semantic Occupancy Prediction For Embodied Scene Understanding
Ruoyu Wang, Yong Liu, Jiahan Li +3
Crucial for autonomous exploration, online 3D occupancy prediction and mapping incrementally construct dense spatial representations on the fly. Embodied online occupancy predictio…
NEWTON: Agentic Planning for Physically Grounded Video Generation
Yuxiang Feng, Juncheng Wang, Chao Xu +7
Video generation models produce visually compelling results but systematically violate physical commonsense -- on VideoPhy-2, the best model achieves only 32.6% joint accuracy. We…
Vision-Centric 4D Occupancy Forecasting and Planning via Implicit Residual World Models
Jianbiao Mei, Yu Yang, Xuemeng Yang +4
End-to-end autonomous driving systems increasingly rely on vision-centric world models to understand and predict their environment. However, a common ineffectiveness in these model…
3D and 4D World Modeling: A Survey
Lingdong Kong, Yu Yang, Jianbiao Mei +20
World modeling has become a cornerstone in AI research, enabling agents to understand, represent, and predict the dynamic environments they inhabit. While prior work largely emphas…
X-Scene: Large-Scale Driving Scene Generation with High Fidelity and Flexible Controllability
Yu Yang, Alan Liang, Jianbiao Mei +3
Diffusion models are advancing autonomous driving by enabling realistic data synthesis, predictive end-to-end planning, and closed-loop simulation, with a primary focus on temporal…
DreamForge: Motion-Aware Autoregressive Video Generation for Multi-View Driving Scenes
Jianbiao Mei, Tao Hu, Xuemeng Yang +7
Recent advances in diffusion models have improved controllable streetscape generation and supported downstream perception and planning tasks. However, challenges remain in accurate…
DQFormer: Towards Unified LiDAR Panoptic Segmentation with Decoupled Queries
Yu Yang, Jianbiao Mei, Liang Liu +6
LiDAR panoptic segmentation, which jointly performs instance and semantic segmentation for things and stuff classes, plays a fundamental role in LiDAR perception tasks. While most…
Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving
Yu Yang, Jianbiao Mei, Yukai Ma +5
World models envision potential future states based on various ego actions. They embed extensive knowledge about the driving environment, facilitating safe and scalable autonomous…