"end-to-end autonomous driving" Papers
10 papers found
Conference
DistillDrive: End-to-End Multi-Mode Autonomous Driving Distillation by Isomorphic Hetero-Source Planning Model
Rui Yu, Xianghang Zhang, Runkai Zhao et al.
ICCV 2025arXiv:2508.05402
4
citations
DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
Shuyao Shang, Yuntao Chen, Yuqi Wang et al.
NEURIPS 2025arXiv:2509.17940
8
citations
DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
Xiaosong Jia, Junqi You, Zhiyuan Zhang et al.
ICLR 2025oralarXiv:2503.07656
70
citations
Embodied Cognition Augmented End2End Autonomous Driving
Ling Niu, Xiaoji Zheng, han wang et al.
NEURIPS 2025arXiv:2511.01334
End-to-End Driving with Online Trajectory Evaluation via BEV World Model
Yingyan Li, Yuqi Wang, Yang Liu et al.
ICCV 2025arXiv:2504.01941
55
citations
HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder
Yingqi Tang, Zhuoran Xu, Zhaotie Meng et al.
ICCV 2025arXiv:2503.08612
12
citations
Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Driving
Peidong Li, Dixiao Cui
ICLR 2025oralarXiv:2409.18341
24
citations
Prioritizing Perception-Guided Self-Supervision: A New Paradigm for Causal Modeling in End-to-End Autonomous Driving
Yi Huang, Zhan Qu, Lihui Jiang et al.
NEURIPS 2025arXiv:2511.08214
1
citations
ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving
Yuhang Lu, Jiadong Tu, Yuexin Ma et al.
ICCV 2025arXiv:2507.12499
6
citations
SynAD: Enhancing Real-World End-to-End Autonomous Driving Models through Synthetic Data Integration
Jongsuk Kim, Jae Young Lee, Gyojin Han et al.
ICCV 2025arXiv:2510.24052