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Lei Zhang Chair
Professor of Computer Vision and Image Analysis Fellow of IEEE Office: PQ816 I am also with OPPO Research Institute. |
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Education
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3/1998~10/2001 |
PhD |
Dept. of Automatic Control,
Northwestern Polytechnical University,
Xi'an, China. |
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9/1995~3/1998 |
M.Sc |
Dept. of Automatic Control,
Northwestern Polytechnical University,
Xi'an, China. |
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9/1991~7/1995 |
B.Sc |
Dept. of Aeronautical
Engineering, Shenyang
Inst. of Aeronautical Engineering, Shenyang, China. |
Work Experience
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7/2017~present |
Chair Professor, Dept. of
Computing, Hong Kong Polytechnic University, Hong Kong. |
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7/2015~6/2017 |
Professor, Dept. of
Computing, Hong Kong Polytechnic University, Hong Kong. |
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9/2010~6/2015 |
Associate Professor, Dept.
of Computing, Hong Kong Polytechnic University, Hong Kong. |
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1/2006~8/2010 |
Assistant Professor, Dept.
of Computing, Hong Kong Polytechnic University, Hong Kong. |
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1/2003~1/2006 |
Postdoctoral Fellow, Dept. of Electrical and Computer
Engineering, McMaster University,
Canada. |
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1/2001~1/2003 |
Research
Assistant/Associate, Dept. of Computing, Hong Kong Polytechnic University,
Hong Kong. |
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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
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News
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1.
Several PhD Student positions jointly trained with OPPO Research Institute are available.
The research topics include Efficient LLM/VLM, Image/Video Restoration/Enhancement/Generation, Agent, etc., Please
send me your CV if you have interest. |
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2.
Several Postdoctoral Fellow or Research Associate positions on Efficient
LLM/VLM, Image/Video
Restoration/Enhancement/Generation, Agent, etc., are available. Please send me your CV if
you have interest. |
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3.
Research
Interns on Efficient LLM/VLM, Agent, Image/Video Enhancement/Quality Assessment/Generation, etc., are
available at OPPO Research Institute. Please send me your CV if you have
interest. |
Newly accepted
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1.
N.
Zhang, S. Wang, J. Zhang, C. Xiao, L. Zhang, "BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language
Models," in NeurIPS 2026. (paper) (code) (To make low-bit LLM faster: 2X speedup with MTP!) |
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2.
Z.
Guo, R. Wu, Q. Yi, C. Xie, X. Wei, L. Zhang, " Two Halves are More than
One: Phase-wise Velocity Distillation for Fast and High-Quality Image
Generation," in NeurIPS 2026. (paper) (code) (Highly effective T2I with single-NFE equivalent inference cost!) |
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3.
Z.
Zhang, L. Sun, R. Wu, Q. Yi, X. Kong, C. Xiao, L. Zhang, "LDM-is-AE:
Latent Diffusion is an Auto-Encoder for End-to-End
Image Generation," in NeurIPS 2026. (paper) (code) (LDM can do image generation by itself
without encoder-decoder!) |
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4.
R.
Cui, S. Liu, R. Wu, L. Zhang, "MESS: Multi-Exposure Sequence Synthesis
for Generalizable Image Enhancement," in NeurIPS
2026. (paper) (code) (Synthesized data can train a generalized image enhancer!) |
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5.
P.
Wang, S. Wang, L. Chen, Z. Ma, G. Zhang, L. Zhang, "DepthMaster:
Unified Monocular Depth Estimation for Perspective and Panoramic
Images," in NeurIPS 2026. (paper) (code) (New SOTA on perspective and panoramic images using a unified
model!) |
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6.
C.
Xie, Y. Wu, Q. Yi, L. Zhang, "Text-Vision Co-Instructed Image
Editing," in NeurIPS 2026. (paper) (code) (Textual and visual prompts together make
your editing more accurate!) |
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7.
G.
Qin, J. Zhang, C. He, J. Liang, T. Wu, Y. Jin, L. Zhang, "Tool-IQA:
Augmenting Image Quality Assessment with Simple Tools," in NeurIPS 2026. (paper) (code) (Magnifier and Gamma corrector are all tools
you need to enhance your IQA model!) |
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8.
Y.
Guo, Z. Zhang, P. Wang, X. Liang, Z. Ma, L. Zhang, "Memorize When
Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video
Generation," in NeurIPS 2026. (paper) (code) (Efficient training for spatially consistent long-horizon video
generation!) |
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9.
S.
Liu, F. Han, J. Liao, Y. Sun, L. Sun, R. Li, X. Wei, J. Liang, H. Zeng, X. Zhang,
L. Zhang, "AURA: An Autonomous Retouching Agent with Photographic Visual
Thinking," in NeurIPS 2026. (paper) (code) (An agent to make your photo professional!) |
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10.
X.
Kong, R. Wu, S. Liu, L. Sun, L. Zhang, "NSARM: Next-Scale Autoregressive
Modeling for Robust Real-World Image
Super-Resolution," in NeurIPS 2026. (paper) (code) (An efficient and robust AR model for
real-world super-resolution!) |
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11.
Y.
Zhong, H. Qin, X. Zhang, L. Zhang, G. Sun, "Breaking Modality
Heterogeneity in Low-Bit Quantization for Large Vision-Language Models,"
in NeurIPS 2026. (paper) (code) (Joint quantization of vision and language
modalities!) |
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12.
X.
Kong, C. Dong and L. Zhang, "Towards Effective Multiple-in-One Image
Restoration: A Sequential and Prompt Learning Strategy," in Machine
Intelligence Research, 2026. (paper) (code) (A simple yet effective prompting strategy
with a MiO-100 benchmark!) |
Preprint
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1.
L.
Sun, R. Wu, X. Kong, J. Zhao, Q. Yi, Y. Sun, S. Liu, Z. Zhang, L. Zhang,
"PixRestore: Unified Image Restoration via
Pixel Diffusion Transformer," preprint. (paper) (code) (Pixel diffusion provides an effective and
efficient solution for unified image restoration!) |
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2.
R.
Li, T. Yang, Z. Ma, F. Ai, S. Wen, L. Zhang, "Avatar-Forever: Decoupled
Parallel Training for High-Quality Real-Time Infinite Avatars,"
preprint. (paper) (code) (Endless high-quality avatar video
generation in real time!) |
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3.
W.
Zhu, Y. Zhang, W. Zeng, L. Zhang, "MMOOC: A Comprehensive Benchmark for
Out-of-Context Evaluation in Multimodal Large Language Models,"
preprint. (paper) (code&data) |
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4.
X.
Kong, J. Zhao, L. Sun, R. Wu, L. Zhang, "GGT-100K: Generative Ground
Truth for Generalizable Real-World Image Restoration," preprint. (paper) (code) (Can multimodal foundation models be the
solution for generalizable real-world image restoration?) |
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5.
R.
Li, T. Yang, F. Ai, T. Wu, S. Wen, B. Peng, Lei Zhang, "Long-Horizon Streaming
Video Generation via Hybrid Attention with Decoupled Distillation,"
preprint. (paper) (code) (Video generation at 29.5 FPS (832X480) on
a single H100 GPU without quantization or model compression!) |
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6.
W.
Li, Z. Qi, Z. Zhao, K. Zhang, L. Zhang, "Weighted Reverse Convolution
for Feature Upsampling," preprint. (paper) (code) (Making the features of vision foundation
models stronger!) |
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7.
Z.
Zheng, C. He, S. Wang, Y. Li, M. Cheng, L. Zhang, "DEL: Digit Entropy
Loss for Numerical Learning of Large Language Models," preprint. (paper) (code) (A simple yet effective loss to improve the
numerical learning capability of LLMs!) |
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8.
H.
Wang, C. Shen, L. Zhang, Z. Cheng, "ATSS: Detecting AI-Generated Videos
via Anomalous Temporal Self-Similarity," preprint. (paper) (code) (A highly effective algorithm to detect
AI-generated videos!) |
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9.
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? ) |
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10. Z. Wang, X. Wei, B. Li, Z. Guo, J. Zhang,
H. Wei, K. Wang, L. Zhang, "VideoVerse: Does
Your T2V Generator Have World Model Capability to Synthesize Videos?"
preprint. (paper) (code) (To evaluate how strong your T2V model is!) |