Lei Zhang

Chair Professor of Computer Vision and Image Analysis

Fellow of IEEE
Department of Computing
The Hong Kong Polytechnic University
Hung Hom, Kowloon, Hong Kong

Office: PQ816
Email: cslzhang at comp.polyu dot edu.hk

I am also with OPPO Research Institute.

3/1998~10/2001

PhD

Dept. of Automatic Control, Northwestern Polytechnical University, Xi'an, China.

9/1995~3/1998

M.Sc

Dept. of Automatic Control, Northwestern Polytechnical University, Xi'an, China.

9/1991~7/1995

B.Sc

Dept. of Aeronautical Engineering, Shenyang Inst. of Aeronautical Engineering, Shenyang, China.

7/2017~present

Chair Professor, Dept. of Computing, Hong Kong Polytechnic University, Hong Kong.

7/2015~6/2017

Professor, Dept. of Computing, Hong Kong Polytechnic University, Hong Kong.

9/2010~6/2015

Associate Professor, Dept. of Computing, Hong Kong Polytechnic University, Hong Kong.

1/2006~8/2010

Assistant Professor, Dept. of Computing, Hong Kong Polytechnic University, Hong Kong.

1/2003~1/2006

Postdoctoral Fellow, Dept. of Electrical and Computer Engineering, McMaster University, Canada.

1/2001~1/2003

Research Assistant/Associate, Dept. of Computing, Hong Kong Polytechnic University, Hong Kong.

Visual Computing Lab (our mission):

Y learning and beyond: for future visual enhancement and understanding.

Papers&Codes

1.    Several PhD Student positions jointly trained with OPPO Research Institute are available. The research topics include Image/Video Restoration/Enhancement, Image/Video Generation, LLM/VLM, Mobile MLLM, etc. Please send me your CV if you have interest.

2.    Several Postdoctoral Fellow or Research Associate positions on Image/Video Generation and Restoration, LLM/VLM, Visual Understanding are available. Please send me your CV if you have interest.

3.    Research Interns on Image/Video Enhancement, Image/Video Quality Assessment, Image/Video Generation, Unified Models, Mobile MLLM, etc., are available at OPPO Research Institute. Please send me your CV if you have interest.

1.      R. Wu, L. Sun, Z. Zhang, X. Kong, J. Zhao, S. Wang, L. Zhang, "VOSR: A Vision-Only Generative Model for Image Super-Resolution," in CVPR 2026. (paper) (code) (Train your strong generative SR models from scratch without using text-image pairs!)

2.      Q. Yi, S. Li, R. Wu, L. Sun, Z. Zhang, L. Zhang, "GDPO-SR: Group Direct Preference Optimization for One-Step Generative Image Super-Resolution," in CVPR 2026. (paper) (code) (Can we apply RL to one-step diffusion SR models?)

3.      C. Xiao, Z. Zhang, L. Zhang, "BinaryAttention: One-Bit QK-Attention for Vision and Diffusion Transformers," in CVPR 2026. (paper) (code) (Extremely low-bit attention without performance degradation!)

4.      L. Chen, P. Wang, G. Zhang, Z. Ma, L. Zhang, "Omni-3DEdit: Generalized Versatile 3D Editing in One-Pass," in CVPR 2026. (paper) (code) (The first generalized 3D editing model, with fast speed!)

5.      X. Wei, K. Cen, H. Wei, Z. Guo, B. Li, Z. Wang, J. Zhang, L. Zhang, "MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition," in CVPR 2026. (paper) (code) (An elaborately constructed dataset and a strong baseline model for multi-image composition!)

6.      S. Wang, G. Chen, D. Huang, Z. Li, M. Li, G. Li, J.M. Alvarez, L. Zhang, Z. Yu, "VideoITG: Improving Multimodal Video Understanding with Instructed Temporal Grounding," in CVPR 2026. (paper) (code) (A plug and play approach and a dataset to improve video understanding tasks!)

7.      X. Liang, Z. Ma, L. Sun, Y. Guo, L. Zhang, "Photo3D: Advancing Photorealistic 3D Generation through Structure‑Aligned Detail Enhancement," in CVPR 2026. (paper) (code) (To make 3D generation results more realistic!)

8.      W. Zhu, Y. Zhang, X. Jin, W. Zeng, L. Zhang, "ANTS: Shaping the Adaptive Negative Textual Space by MLLM for OOD Detection," in CVPR 2026. (paper) (code) (Can MLLM help OOD detection?)

9.      L. Qu, S. Zhou, J. Liang, H. Zeng, L. Zhang, J. Yang, "It Takes Two: A Duet of Periodicity and Directionality for Burst Flicker Removal," in CVPR 2026. (paper) (code) (To capture your precious moment without annoying flickers!)

10.  P. Wang, L. Chen, Z. Ma, Y. Guo, G. Zhang, L. Zhang, "One2Scene: Geometric Consistent Explorable 3D Scene Generation from a Single Image," in ICLR 2026. (paper) (code) (Generating an explorable 3D scene from a single image!)

11.  T. Yang, R. Li, Y. Shi, Y. Zhang, Q. Dong, H. Cheng, W. Feng, S. Wen, B. Peng, L. Zhang, "Many-for-Many: Unify the Training of Multiple Video and Image Generation and Manipulation Tasks," in ICLR 2026. (paper) (code) (One model, many tasks!)

1.      Y. Wu, C. Xie, R. Li, L. Chen, Q. Yi, L. Zhang, "CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning," preprint. (paper) (code) (Edit the image as you instruct without changing the background details!)

2.      L. Sun, R. Wu, Z. Zhang, R. Li, Y. Sun, S. Liu, L. Zhang, "Self-transcendence: Is External Feature Guidance Indispensable for Accelerating Diffusion Transformer Training?" preprint. (paper) (code) (Do we really need pre-trained external feature representations to accelerate DiT training?)

3.      T. Wu, R. Li, L. Zhang, K. Ma, "Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesis," preprint. (paper) (code) (Completely address the loss of diversity in DMD distillation!)

4.      J. Zhang, C. Xiao, A. Wu, X. Zhang, L. Zhang, "Pretraining A Large Language Model using Distributed GPUs: A Memory-Efficient Decentralized Paradigm," preprint. (paper) (code) (Can we train large-scale LLMs using GPUs with low memory? )

5.      K. Guan, R. Wu, S. Li, W. Zhu, W. Zeng, L. Zhang, "Restoration Adaptation for Semantic Segmentation on Low Quality Images," preprint. (paper) (code) (Effective segmentation on real-world low-quality images!)

6.      Z. Wang, K. Wang, L. Zhang, "PhyDetEx: Detecting and Explaining the Physical Plausibility of T2V Models," preprint. (paper) (code) (Is the generated video physically plausible and why?)

7.      Z. Wang, X. Wei, B. Li, Z. Guo, J. Zhang, H. Wei, K. Wang, L. Zhang, "VideoVerse: How Far is Your T2V Generator from a World Model?" preprint. (paper) (code) (To evaluate how strong your T2V model is!)

8.      X. Kong, R. Wu, S. Liu, L. Sun, L. Zhang, "NSARM: Next-Scale Autoregressive Modeling for Robust Real-World Image Super-Resolution," preprint. (paper) (code) (An efficient and robust AR model for real-world super-resolution!)

9.      X. Wei, J. Zhang, Z. Wang, H. Wei, Z. Guo, L. Zhang, "TIIF-Bench: How Does Your T2I Model Follow Your Instructions?" preprint. (paper) (code) (To accurately evaluate T2I models' real performance!)