Wenbo Ji   嵇jī / yí文博

I am a second year master's student in Electrical Engineering and Information Technology at the Technical University of Munich.

I was working as a working student at ImFusion with Mert Asim Karaoglu, Dr. Benjamin Busam, Prof. Nassir Navab, Dr. Alexander Ladikos.

I was a master's student of TUM-CVG, TUM-DI-LAB working with Prof. Daniel Cremers, Dr. Yan Xia, Dr. Chuanxia Zheng and Weirong Chen.

I did a research internship at Zhejiang University under the supervision of Prof. Yiyi Liao.

I obtained my Master’s degree in Computer Science from the Tongji University.

I did my B.Sc. in Information and Computing Science at Nanjing Tech University.

My research interests lie at the intersection of computer vision, computer graphics, and machine learning -- creating virtual human models and representing 3D scenes.

If you find any research interests that we might share, feel free to drop me an email.

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• [08/2025] Our paper CSG-Fusion is accepted by ICCV 2025 E2E3D Workshop.


• [07/2025] I graduated from Tongji University with a Master’s degree in Computer Science! 🎓


• [06/2025] Our paper LiteTracker is accepted by MICCAI 2025.


• [01/2025] Our paper Re0 is accepted by ICRA 2025.

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[08/2024] I will join Imfusion as a working student on the topic of Dense Video Point Tracking.


[01/2024] I will join TUM-CVG, TUM-DI-LAB under the co-supervision of Dr. Yan Xia and Dr. Chuanxia Zheng.


[05/2023] I will join Technische University München in the winter semester 23/24 as a Master student in Electrical Engineering, see you in München🍻!

Much of my research is about inferring the physical world (shape, motion, color, etc) from images and 3D raw data.

A feed-forward framework that mindfully integrates pixel-aligned pointmap to reduce redundant primitives and produce compact and consistent 3D structures.

A low-latency method for tissue online tracking in endoscopic video streams, introduces a set of training-free runtime optimizations on a state-of-the-art long-term point tracking method.

Given 3D point clouds and multi-view RGB-D images with poses, Re0 leverages the 3D geometric information, projection relationships and CLIP semantic features for 3D zero-shot instance segmentation.