I am a tenure-track Associate Professor at the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. Previously, I received my Ph.D. from the Computer Vision Lab, Department of Information Technology and Electrical Engineering, ETH Zurich, under the supervision of Prof. Luc Van Gool. I worked closely with Prof. Radu Timofte, Prof. Kai Zhang and Prof. Yulun Zhang. After my Ph.D., I was a postdoctoral researcher at Harvard University working with Prof. Yogesh Rathi.

My research interests include image restoration, generative models, multimodal large language models, and efficient diffusion models. I have published papers in ICML, NeurIPS, CVPR, ICCV, ECCV, and TPAMI. My work has been cited over 10000 times (Google Scholar). I was a recipient of the Best Paper Prize at the ICCV Advances in Image Manipulation (AIM) Workshop 2021, a Guest Editor of Electronics, and in 2021 was listed among Baidu's Top 100 Most Promising Chinese Students in Artificial Intelligence. According to ScholarGPS, my research in super-resolution imaging has ranked among the top 1.05% globally in impact over the past 5 years.

I am actively looking for highly motivated undergraduate, master's, and PhD students to join my research group. If you are interested, please send your CV, transcripts, and a brief research statement to caojiezhang@sjtu.edu.cn.

Unleashing the Power of One-Step Diffusion based Image Super-Resolution via a Large-Scale Diffusion Discriminator

Jianze Li, Jiezhang Cao*, Zichen Zou, Xiongfei Su, Xin Yuan, Yulun Zhang, Yong Guo, Xiaokang Yang

NeurIPS 2025

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One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation

Jianze Li, Jiezhang Cao*, Yong Guo, Wenbo Li, Yulun Zhang

ICML 2025

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Deep Equilibrium Diffusion Restoration with Parallel Sampling

Jiezhang Cao, Yue Shi, Kai Zhang, Yulun Zhang, Radu Timofte, Luc Van Gool

CVPR 2024

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CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution

Jiezhang Cao, Qin Wang, Yongqin Xian, Yawei Li, Bingbing Ni, Zhiming Pi, Kai Zhang, Yulun Zhang, Radu Timofte, Luc Van Gool

CVPR 2023

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Improving Generative Adversarial Networks with Local Coordinate Coding

Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan

TPAMI 2022

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SwinIR: Image Restoration Using Swin Transformer

Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, Radu Timofte

ICCV Workshop 2021 (Best Paper Award)

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Multi-marginal Wasserstein GAN

Jiezhang Cao, Langyuan Mo, Yifan Zhang, Kui Jia, Chunhua Shen, Mingkui Tan

NeurIPS 2019

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Adversarial Learning with Local Coordinate Coding

Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan

ICML 2018

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Reference-based Image Super-Resolution with Deformable Attention Transformer

Jiezhang Cao, Jingyun Liang, Kai Zhang, Yawei Li, Yulun Zhang, Wenguan Wang, and Luc Van Gool

ECCV 2022

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Towards Interpretable Video Super-Resolution via Alternating Optimization

Jiezhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, and Luc Van Gool

ECCV 2022

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VRT: A Video Restoration Transformer

Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool

IEEE TIP 2024

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Video Super-resolution Transformer

arXiv 2021

Jiezhang Cao, Yawei Li, Jingyun Liang, Kai Zhang, Luc Van Gool

Paper | Code