Wentao Cheng
Associate Professor
Beijing Normal-Hong Kong Baptist University
Email: wentaocheng@bnbu.edu.cn
I am an Associate Professor at Beijing Normal-Hong Kong Baptist University (BNBU).
Prior to joining BNBU in Feb 2025, I worked as an Associate Professor at Nankai University (2022–2024) and as a Senior Algorithm Engineer at Alibaba Group AI Lab (2020–2022).
I received my Joint Ph.D. degree in Computer Science and Engineering from Nanyang Technological University (NTU), Singapore, and Technische Universität Darmstadt, Germany. I obtained my B.Eng. degree from Harbin Institute of Technology (HIT).
My research interests lie in 3D Computer Vision, with a particular focus on:
- Visual Localization
- 3D Reconstruction
- Efficient Feed-Forward 3D Foundation Models
I actively serve as a reviewer for top-tier conferences and journals, including CVPR, ICCV, ECCV, ICRA, TIP, and TRO. Additionally, I serve as an Executive Committee Member of the Technical Committee on CAD and Computer Graphics (CAD/CG), China Computer Federation (CCF).
news
| Mar 18, 2026 | Two papers on 3D Foundation Models and Local Feature Learning have been accepted by ICME 2026! 🎉🎉
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| Dec 16, 2025 | I served as the Lead Organizer for the CCF CAD&CG Academic Seminar (BNBU Station). We invited four distinguished experts to discuss Visual Perception and Graphics. |
| Oct 01, 2025 | One paper titled “Beyond Flat Text: Dual Self-inherited Guidance for Visual Text Generation” was accepted to ICCV Workshops (HiGen) 2025. |
| Feb 01, 2025 | I joined Beijing Normal-Hong Kong Baptist University (BNBU) as an Associate Professor! |
| Feb 27, 2024 | One paper titled “ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction” was accepted to CVPR 2024. |
selected publications
- ICMES-VGGT: Structure-Aware Subscene Decomposition for Scalable 3D Foundation ModelsIn IEEE International Conference on Multimedia and Expo (ICME), 2026
- ICMED2Feat: Dual Distillation for Semantic and Geometric Local Feature LearningIn IEEE International Conference on Multimedia and Expo (ICME), 2026
- TIPA Data-Driven Point Cloud Simplification Framework for City-Scale Image-Based LocalizationIEEE Transactions on Image Processing (TIP), 2017