iMUSE Lab
intelligent MUlti-Sensing lab — where “MUSE” also means inspiration.
iMUSE Lab is a computer vision research group at Shenzhen University working on multi-view crowd intelligence, robust 3D scene understanding, and camera-only 4D occupancy forecasting.
The lab has 4 Ph.D. and 9 master’s students. The 7 who have graduated went to Ph.D. programs (Shenzhen University, NJUPT) or to Huawei, Bilibili, Qihoo 360 and Alibaba’s Linxi Games.
Group photo, 2025.
Principal Investigator
Associate Professor (Tenured) and doctoral supervisor, Shenzhen University. Founder and principal investigator of iMUSE Lab. Research: multi-view crowd intelligence, robust 3D scene understanding, and dynamic-scene modelling.
Research by group members
All 27 papers →Six papers across the lab’s directions with group members as first author or key contributor; bold marks the group members.
Ph.D. Students
Master’s Students
Alumni
| Name | Degree | Next |
|---|---|---|
| Yunfei Gong | M.Eng. 2022.04-2024.06 | Ph.D. at Shenzhen University |
| Zhidan Xie | M.Eng. 2022.04-2024.06 | Qihoo 360 |
| Daijie Chen | M.Eng. 2022.09-2025.06 | Linxi Games (Alibaba) |
| Kaiyi Zhang | M.Eng. 2022.09-2025.06 | Ph.D. at Shenzhen University |
| Zhouhang Luo | M.Eng. 2022.09-2025.06 | Huawei |
| Bin Li | M.Eng. 2023.09-2026.06 | Ph.D. at NJUPT |
| Tao Yu | M.Eng. 2023.09-2026.06 | Bilibili |
Join iMUSE
We take Ph.D. and master’s students every year. Prospective students normally join one of three efforts: crowd simulation and generation, multi-view 3D reconstruction, or 4D occupancy forecasting from cameras only. We also host motivated undergraduates on research or competition projects — computer vision, embedded AI and mobile application work — with the opportunity to develop that work toward a publication when it is ready. Undergraduates working with us have won provincial competition prizes and had graduation projects selected among the university’s outstanding undergraduate theses.
Ph.D. intake. The 2026 quota is full. Enquiries for 2027 are welcome now; pre-admission follows the college’s own schedule, and university and college scholarships are available. Write to qizhang@szu.edu.cn, my institutional address and the one the college’s admissions office recognises.
What matters to us: you can read a paper and reproduce part of it, you are comfortable with PyTorch and geometry, and you are willing to build reproducible research and release code or data when appropriate. If that describes you, write to qi.zhang.opt@gmail.com with a transcript, one project you are proud of, and which of the three above you want to work on.
Past calls: 2024 (PDF) · 2023 (PDF). The earlier version of this page was built with the help of my wife. Thank you.