Scholar
Peizheng Li
Google Scholar ID: SExOc74AAAAJ
Mercedes-Benz AG R&D & University of Tuebingen
Citations & Impact
Citations
69
H-index
3
i10-index
2
Publications
7
Co-authors
14
list available
Publications
Resume (English only)
Academic Achievements
- Publications:
- - AGO: Adaptive Grounding for Open World 3D Occupancy Prediction, ICCV 2025
- - SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving, ECCV 2024 (1st ranking on Argoverse 2 Self-supervised scene flow leaderboard)
- - PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird’s-Eye View, IJCAI 2023
- Preprints:
- - TQD-Track: Temporal Query Denoising for 3D Multi-Object Tracking, arXiv 2025
- - FAM-HRI: Foundation-Model Assisted Multi-Modal Human-Robot Interaction Combining Gaze and Speech, arXiv 2025
- - SEER-VAR: Semantic Egocentric Environment Reasoner for Vehicle Augmented Reality, arXiv 2025
Research Experience
- Currently a Ph.D. student with the Scene Understanding Group at Mercedes-Benz R&D, as well as the Cognitive Systems Group at the University of Tübingen.
Education
- Ph.D.: University of Tübingen, Cognitive Systems Group, advised by Prof. Andreas Geiger and Prof. Andreas Zell; M.S.: University of Stuttgart, Electromobility, research thesis at the Institute of Signal Processing and System Theory, supervised by Prof. Bin Yang; B.S.: Tongji University, Automotive Studies.
Background
- Research Interests: Machine learning, vision, robotics, and autonomous driving. Professional Field: Scene understanding.
