10 papers
DVGT: Driving Visual Geometry Transformer
Sicheng Zuo, Zixun Xie, Wenzhao Zheng +6
Perceiving and reconstructing 3D scene geometry from visual inputs is crucial for autonomous driving. However, there still lacks a driving-targeted dense geometry perception model…
DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale
Sicheng Zuo, Zixun Xie, Wenzhao Zheng +6
End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models, which focus on learning language descr…
Vega: Learning to Drive with Natural Language Instructions
Sicheng Zuo, Yuxuan Li, Wenzhao Zheng +3
Vision-language-action models have reshaped autonomous driving to incorporate languages into the decision-making process. However, most existing pipelines only utilize the language…
DriveTok: 3D Driving Scene Tokenization for Unified Multi-View Reconstruction and Understanding
Dong Zhuo, Wenzhao Zheng, Sicheng Zuo +4
With the growing adoption of vision-language-action models and world models in autonomous driving systems, scalable image tokenization becomes crucial as the interface for the visu…
EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene Understanding
Yuqi Wu, Wenzhao Zheng, Sicheng Zuo +3
3D occupancy prediction provides a comprehensive description of the surrounding scenes and has become an essential task for 3D perception. Most existing methods focus on offline pe…
QuadricFormer: Scene as Superquadrics for 3D Semantic Occupancy Prediction
Sicheng Zuo, Wenzhao Zheng, Xiaoyong Han +3
3D occupancy prediction is crucial for robust autonomous driving systems as it enables comprehensive perception of environmental structures and semantics. Most existing methods emp…