|
Lei Zhang Chair
Professor of Computer Vision and Image Analysis Fellow of IEEE Office: PQ816 I am also with OPPO Research Institute. |
|
Education
|
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. |
Work Experience
|
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. |
My Google Scholar Citation Profile:
http://scholar.google.com/citations?user=tAK5l1IAAAAJ
|
|
|
![MC900297235[1]](index_files/image009.gif)
News
|
1.
Our
following paper was selected as the "2024 IEEE SPS Best Paper
Award": K.
Zhang, W. Zuo, L. Zhang, "FFDNet:
Toward a Fast and Flexible Solution for CNN based Image Denoising," IEEE Trans. on Image Processing, vol. 27, issue 9, pp. 4608-4622,
Sept. 2018. |
|
2.
Several PhD Student positions jointly trained with OPPO Research Institute are available.
The research topics include Image/Video
Restoration/Enhancement, Image/Video Quality Assessment, Diffusion Models,
Vision-Language Models, Efficient Network Architectures, etc. Please send me your CV if you have
interest. |
|
3.
Several Postdoctoral Fellow or Research Associate positions on Image/Video Generation and Restoration,
Image/Video Quality Assessment, Vision-Language Models are available. Please send me your CV if
you have interest. |
|
4.
Research
Interns on Image/Video Enhancement, Image/Video Quality Assessment, Diffusion
Models, Vision-Language Models, etc., are available at OPPO
Research Institute. Please send me your CV if
you have interest. |
Newly accepted
|
1.
Q.
Yi, S. Li, R. Wu, L. Sun, Y. Wu, L. Zhang, "Fine-structure Preserved
Real-world Image Super-resolution via Transfer VAE Training," in ICCV
2025. (paper) (code) (We re-train the VAE of SD2.1 while maintaining its UNet for more
precise Real-ISR!) |
|
2.
H.
Wei, S. Liu, C. Yuan, L. Zhang, "Perceive, Understand and Restore:
Real-World Image Super-Resolution with Autoregressive Multimodal Generative
Models," in ICCV 2025. (paper) (code) (Can autoregressive multimodal models do
generative image restoration?) |
|
3.
D.
Chen, L. Chen, Z. Zhang, L. Zhang, "Generalized and Efficient 2D
Gaussian Splatting for Arbitrary-Scale Super-Resolution," in ICCV 2025. (paper) (code) (Effective and efficient ASR with GS representation!) |
|
4.
Z.
Guo, M. Liu, Q. Wang, Z. Ji, J. Bai, L. Zhang, W. Zuo, "Integrating Visual Interpretation and Linguistic Reasoning
for Geometric Problem Solving," in ICCV 2025. (paper) (code) (How to utilize visual information for solving geometric problems!) |
|
5.
Y.
Wu, L. Chen, R. Li, S. Wang, C. Xie, L. Zhang, "InsViE-1M: Effective
Instruction-based Video Editing with Elaborate Dataset Construction," in
ICCV 2025. (paper) (code) (A large-scale instruction-based video
editing dataset and an effective model!) |
|
6.
M.
Li, C. Xie, Y. Wu, L. Zhang, M. Wang, "FiVE: A Fine-grained Video
Editing Benchmark for Evaluating Emerging Diffusion and Rectified Flow
Models," in ICCV 2025. (paper) (code&data) (A timely benchmark for video editing!) |
|
7.
X.
Huang, S. Liu, K. Zhang, Y. Tai, J. Yang, H. Zeng, L. Zhang, "Reverse
Convolution and Its Applications to Image Restoration," in ICCV 2025. (paper) (code) (A new operator for designing image restoration networks!) |
|
8.
W.
Li, Y. Yuan, J. Liu, D. Tang, S. Wang, J. Zhu, L. Zhang, "TokenPacker:
Efficient Visual Projector for Multimodal LLM," International Journal
of Computer Vision, 2025. (paper) (code) (Up to 89% visual token compression!) |
|
9.
D.
Chen, T. Wu, K. Ma, L. Zhang, "Toward Generalized Image Quality
Assessment: Relaxing the Perfect Reference Quality Assumption," in CVPR
2025. (paper) (code) (General image quality assessment in the era of generative models!) |
|
10.
L.
Sun, R. Wu, Z. Ma, S. Liu, Q. Yi, L. Zhang, "Pixel-level and
Semantic-level Adjustable Super-resolution: A Dual-LoRA Approach," in
CVPR 2025. (paper) (code) (Flexible super-resolution to meet you
preference! Deployed in OPPO Find X8 Ultra smartphone cameras!) |
|
11.
C.
Xie, M. Li, H. Zeng, J. Luo, L. Zhang, "MaSS13K: A Matting-level Semantic
Segmentation Benchmark," in CVPR 2025. (paper) (code) (High resolution and high precision
semantic segmentation dataset and model!) |
|
12.
Z.
Ma, X. Liang, R. Wu, X. Zhu, Z. Lei, L. Zhang, "Progressive Rendering
Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation
without 3D Data," in CVPR 2025. (paper) (code) (Faster and stronger 3D generator!) |
|
13. R. Li, T. Yang, S. Guo, L. Zhang,
"RORem: Training a Robust Object Remover with Human-in-the-Loop,"
in CVPR 2025. (paper) (code) (A powerful remove any object model with a large scale
paired dataset!) |
|
14. B. Chen, G. Li, R. Wu, X. Zhang, J. Chen,
J. Zhang, L. Zhang, "Adversarial Diffusion Compression for Real-World
Image Super-Resolution," in CVPR 2025. (paper) (code) (Extremely efficient generative
super-resolution!) |
|
15. G. Li, B. Chen, C. Zhao, L. Zhang, J.
Zhang, "OSMamba: Omnidirectional Spectral Mamba with Dual-Domain Prior
Generator for Exposure Correction," in CVPR 2025. (paper) (code) |
Preprint
|
1. 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," preprint. (paper) (code) (A plug and play approach to improve video understanding
tasks!) |
|
2. W. Lin, X. Wei, R. An, T. Ren, T. Chen, R.
Zhang, Z. Guo, W. Zhang, L. Zhang, H. Li, "Perceive Anything: Recognize,
Explain, Caption, and Segment Anything in Images and Videos," preprint. (paper) (code) (A perceive anything model with large-scale
dataset!) |
|
3. Y. Sun, L. Sun, S. Liu, R. Wu, Z. Zhang,
L. Zhang, "One-Step Diffusion for Detail-Rich and Temporally Consistent
Video Super-Resolution," preprint. (paper) (code) (Address the dilemma in VSR via dual LoRA learning!) |
|
4. 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!) |
|
5. 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," preprint. (paper) (code) (One model, many tasks!) |
|
6. C. Xie, M. Li, S. Li, Y. Wu, Q. Yi, L.
Zhang, "DNAEdit: Direct Noise Alignment for Text-Guided Rectified Flow
Editing," preprint. (paper) (code) (High quality editing with accurate background preservation!) |
|
7. T. Wu, J. Zou, J. Liang, L. Zhang, K. Ma,
"VisualQuality-R1: Reasoning-Induced Image Quality Assessment via
Reinforcement Learning to Rank," preprint. (paper) (code) (A strong no-reference quality assessment
model with reasoning!) |
|
8. X. Liang, Z. Ma, L. Sun, Y. Guo, L.
Zhang, "AlignCVC: Aligning Cross-View Consistency for Single-Image-to-3D
Generation," preprint. (paper) (code) (A new pipeline for single-image-to-3D generation!) |
|
9. S. Liu, J. Ma, L. Sun, X. Kong, L. Zhang,
"InstructRestore: Region-Customized Image Restoration with Human
Instructions," preprint. (paper) (code) (Restore the image as you wish!) |
|
10. L. Sun, R. Wu, Z. Zhang, H. Yong, L.
Zhang, "Improving the Stability of Diffusion Models for Content
Consistent Super-Resolution," preprint. (paper) (code) |
|
11. X. Kong, C. Dong, L. Zhang, "Towards Effective Multiple-in-One Image
Restoration: A Sequential and Prompt Learning Strategy," preprint. (paper) (code&data) |