詹锟 | Kun Zhan

🔭 About Me

Hello, I’m Kun Zhan. I currently serve as the Cognitive Intelligence Lead at Li Auto, where I lead a team focused on the research and implementation of cognitive models, world models, and reinforcement learning.

My research “ambitions” are vast: autonomous driving, computer vision, 3D vision, large language models, embodied intelligence… Essentially, I’m passionate about any technology that can make vehicles “smarter”! I’m particularly fascinated by implementing cutting-edge AI technologies into robots and vehicles, turning science fiction scenarios into reality and working toward an autonomous future.

For me, technological innovation isn’t just about theoretical breakthroughs—it’s about practical applications that can genuinely transform how people travel. I hope to contribute to the advancement of autonomous driving technology through continuous exploration.

🌟 Research Interests

• Autonomous Driving: End-to-end autonomous driving systems, decision-making and planning
• Computer Vision: Object detection and tracking, scene understanding
• 3D Vision: 3D perception, reconstruction, and modeling
• Large Language Models: Applications of multimodal large models in autonomous driving
• World Models: Environment modeling and prediction, reinforcement learning

💼 Work Experience

Li Auto | April 2021 - Present

Cognitive Intelligence Lead, directing a team in developing cutting-edge autonomous driving technologies, with a focus on cognitive models, world models, and reinforcement learning research and implementation.

Baidu | April 2016 - March 2021

Autonomous Driving Researcher, involved in developing computer vision and artificial intelligence solutions for autonomous vehicles.

📚 Academic Achievements

Citation Statistics

• Total Citations: 465
• h-index: 9
• i10-index: 8

Selected Publications

1. Drivevlm: The convergence of autonomous driving and large vision-language models (2024) X Tian, J Gu, B Li, Y Liu, Y Wang, Z Zhao, K Zhan, P Jia, X Lang, H Zhao arXiv preprint arXiv:2402.12289 | Citations: 107

2. Street gaussians: Modeling dynamic urban scenes with gaussian splatting (2024) Y Yan, H Lin, C Zhou, W Wang, H Sun, K Zhan, X Lang, X Zhou, S Peng European Conference on Computer Vision, 156-173 | Citations: 102

3. Planagent: A multi-modal large language agent for closed-loop vehicle motion planning (2024) Y Zheng, Z Xing, Q Zhang, B Jin, P Li, Y Zheng, Z Xia, K Zhan, X Lang, D Zhao arXiv preprint arXiv:2406.01587 | Citations: 12

4. Tod3cap: Towards 3d dense captioning in outdoor scenes (2024) B Jin, Y Zheng, P Li, W Li, Y Zheng, S Hu, X Liu, J Zhu, Z Yan, H Sun, K Zhan, X Lang, P Jia European Conference on Computer Vision, 367-384 | Citations: 10

5. Unleashing generalization of end-to-end autonomous driving with controllable long video generation (2024) E Ma, L Zhou, T Tang, Z Zhang, D Han, J Jiang, K Zhan, P Jia, X Lang, K Yu arXiv preprint arXiv:2406.01349 | Citations: 9

Patents

• 16 Chinese Patents
• 2 US Patents

Academic Service

• Program Committee/Reviewer: CVPR, ICCV, ECCV, NeurIPS, AAAI
• Journal Reviewer: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Intelligent Transportation Systems (T-ITS), IEEE Transactions on Intelligent Vehicles (T-IV)
• Workshop Organizer: Autonomous Driving Workshop at CVPR 2023