4 papers
Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving
Linhan Wang, Zichong Yang, Chen Bai +6
End-to-end autonomous driving increasingly leverages self-supervised video pretraining to learn transferable planning representations. However, pretraining video world models for s…
From Uncertainty to Stability and Fidelity: Guiding Sparse-View 3D Gaussian Splatting with Fisher Information
Junbao Zhou, Qingshan Xu, Yuan Zhou +7
3D Gaussian Splatting (3DGS) has emerged as a promising technique for novel view synthesis. However, 3DGS requires dense input views to achieve high-quality rendering. In sparse-vi…
DrivePTS: A Progressive Learning Framework with Textual and Structural Enhancement for Driving Scene Generation
Zhechao Wang, Yiming Zeng, Lufan Ma +4
Synthesis of diverse driving scenes serves as a crucial data augmentation technique for validating the robustness and generalizability of autonomous driving systems. Current method…
NavigScene: Bridging Local Perception and Global Navigation for Beyond-Visual-Range Autonomous Driving
Qucheng Peng, Chen Bai, Guoxiang Zhang +5
Autonomous driving systems have made significant advances in Q&A, perception, prediction, and planning based on local visual information, yet they struggle to incorporate broader n…