10 papers
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…
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…
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…
GaussianWorld: Gaussian World Model for Streaming 3D Occupancy Prediction
Sicheng Zuo, Wenzhao Zheng, Yuanhui Huang +2
3D occupancy prediction is important for autonomous driving due to its comprehensive perception of the surroundings. To incorporate sequential inputs, most existing methods fuse re…
GaussianAD: Gaussian-Centric End-to-End Autonomous Driving
Wenzhao Zheng, Junjie Wu, Yao Zheng +8
Vision-based autonomous driving shows great potential due to its satisfactory performance and low costs. Most existing methods adopt dense representations (e.g., bird's eye view) o…
Doe-1: Closed-Loop Autonomous Driving with Large World Model
Wenzhao Zheng, Zetian Xia, Yuanhui Huang +3
End-to-end autonomous driving has received increasing attention due to its potential to learn from large amounts of data. However, most existing methods are still open-loop and suf…
GPD-1: Generative Pre-training for Driving
Zixun Xie, Sicheng Zuo, Wenzhao Zheng +5
Modeling the evolutions of driving scenarios is important for the evaluation and decision-making of autonomous driving systems. Most existing methods focus on one aspect of scene e…
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…