Xiang Li

Tsinghua University Incoming PhD Student, College of AI, Tsinghua University

I am currently an incoming PhD student at CollegeAI, THU, advised by Prof. Yaqin Zhang. I am also an intern of AIR, THU and TARS. Previously, I received my B.Eng. degree from Dept. of Computer Sci. & Tech., THU.
My research interests include 3D Scene Understanding, Autonomous Driving and Embodied AI.


Education
  • Tsinghua University

    Tsinghua University

    B.Eng. in Computer Science Sep. 2021 - Jun. 2025

Honors & Awards
  • Outstanding Graduate of Department 2025
  • Tsinghua Excellent Academic Scholarship 2022 / 2023 / 2024
  • Tsinghua Excellent Art Scholarship 2022 / 2023
  • Tsinghua Freshman Scholarship 2021
Experience
  • TARS

    TARS

    Research Intern Feb. 2025 - Now

  • Institute for AI Industry Research, Tsinghua University

    Institute for AI Industry Research, Tsinghua University

    Research Intern Sep. 2023 - Now

  • HKU Musketeers Foundation Institute of Data Science

    HKU Musketeers Foundation Institute of Data Science

    Student Research Assistant Jul. 2024 - Sept. 2024

News
2025
I started my internship as a Research Intern at TARS.
Feb 08
One paper on 3D Occupancy Prediction and 4D Occupancy Forecasting is accepted by ICLR 2025.
Jan 22
2024
One paper on 3D Occupancy Prediction is accepted by ICRA 2024.
Jan 29
Selected Publications (view all )
Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving
Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving

Xiang Li, Pengfei Li, Yupeng Zheng, Wei Sun, Yan Wang, Yilun Chen

International Conference on Learning Representations (ICLR) 2025

Our semi-supervised 3D occupancy world model, featuring 2D rendering supervision and an end-to-end architecture, can forecast future occupancy straightly from image inputs while taking advantage of 2D labels.

Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving
Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving

Xiang Li, Pengfei Li, Yupeng Zheng, Wei Sun, Yan Wang, Yilun Chen

International Conference on Learning Representations (ICLR) 2025

MonoOcc: Digging into Monocular Semantic Occupancy Prediction
MonoOcc: Digging into Monocular Semantic Occupancy Prediction

Yupeng Zheng*, Xiang Li*, Pengfei Li, Yuhang Zheng, Bu Jin, Chengliang Zhong, Xiaoxiao Long, Hao Zhao, Qichao Zhang(* equal contribution)

International Conference on Robotics and Automation (ICRA) 2024

By proposing a distillation module to transfer temporal information and richer knowledge to the monocular branch from a privileged branch, we increase the performance of the framework especially on small and long-tailed objects, while striking a balance between performance and efficiency.

MonoOcc: Digging into Monocular Semantic Occupancy Prediction
MonoOcc: Digging into Monocular Semantic Occupancy Prediction

Yupeng Zheng*, Xiang Li*, Pengfei Li, Yuhang Zheng, Bu Jin, Chengliang Zhong, Xiaoxiao Long, Hao Zhao, Qichao Zhang(* equal contribution)

International Conference on Robotics and Automation (ICRA) 2024

All publications