ADLab of Shanghai AI Lab

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This is the official website of ADLab (ADG at Shanghai AI Laboratory).

As a research team affiliated with the Shanghai Artificial Intelligence Laboratory, ADLab is primarily focused on cutting-edge research in autonomous driving. Our current endeavor involves developing the next-generation autonomous driving system by integrating human knowledge and common sense. We believe that the knowledge-driven paradigm will elevate the reliability and generalizability of autonomous driving system to a new level.

Now we have about 20 faculty members and 20+ interns (including full-time research interns and joint Ph.D. students). Join us and writing the pages of history.

news

selected publications

  1. arXiv
    DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
    Licheng Wen, Daocheng Fu, Xin Li, Xinyu Cai, Tao Ma, Pinlong Cai, Min Dou, Botian Shi, Liang He, and Yu Qiao
    arXiv preprint arXiv:2309.16292, 2023
  2. arXiv
    Drive like a human: Rethinking autonomous driving with large language models
    Daocheng Fu, Xin Li, Licheng Wen, Min Dou, Pinlong Cai, Botian Shi, and Yu Qiao
    arXiv preprint arXiv:2307.07162, 2023
  3. NeurIPS
    RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection
    Yeqi Bai, Ben Fei, Youquan Liu, Tao Ma, Yuenan Hou, Botian Shi, and Yikang Li
    Advances in Neural Information Processing Systems, 2023
  4. NeurIPS
    AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset
    Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen, Botian Shi, Yikang Li, and Yu Qiao
    Advances in Neural Information Processing Systems, 2023
  5. ITSC
    LimSim: A Long-term Interactive Multi-scenario Traffic Simulator
    Licheng Wen, Daocheng Fu, Song Mao, Pinlong Cai, Min Dou, and Yikang Li
    IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2023
  6. ICCV
    DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds
    Tao Ma, Xuemeng Yang, Hongbin Zhou, Xin Li, Botian Shi, Junjie Liu, Yuchen Yang, Zhizheng Liu, Liang He, Yu Qiao, Yikang Li, and Hongsheng Li
    In Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
  7. CVPR
    Uni3D: A Unified Baseline for Multi-dataset 3D Object Detection
    Bo Zhang, Jiakang Yuan, Botian Shi, Tao Chen, Yikang Li, and Yu Qiao
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
  8. CVPR
    Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection
    Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen, Botian Shi, Yikang Li, and Yu Qiao
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
  9. CVPR
    LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion
    Xin Li, Tao Ma, Yuenan Hou, Botian Shi, Yucheng Yang, Youquan Liu, Xingjiao Wu, Qin Chen, Yikang Li, Yu Qiao, and Liang He
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
  10. ICRA
    Joint Camera Intrinsic and Lidar-Camera Extrinsic Calibration
    Guohang Yan, Feiyu He, Chunlei Shi, Xinyu Cai, and Yikang Li
    International Conference on Robotics and Automation (ICRA), 2023