Jiezhang Cao

Jiezhang Cao

Ph.D. student

ETH Zürich

Biography

I am a Ph.D. student supervised by Prof. Luc Van Gool at Computer Vision Laboratory, ETH Zürich. I also work closely with Dr. Kai Zhang and Dr. Yulun Zhang. My main research interest is the low-level vision, especially on the image and video restoration, such as super-resolution, deblurring and denoising. Besides, I enjoy applying mathematics in proposed methods. Recently, I have some paper published in NeurIPS, ICML, TPAMI, CVPR and ACML. I served as the reviewer for several top-tier conferences, such as NeurIPS, ICLR CVPR and AAAI, etc.

Recent News

  • Two papers was accepted by ECCV 2022.
  • SwinIR is awarded the best paper prize in ICCV-AIM2021.
  • I join the Computer Vision Lab as a Ph.D. student at ETH Zürich.
  • One journal paper was accepted by TPAMI 2020.
  • One conference paper was accepted by CVPR 2020.
  • One conference paper was accepted by NeurIPS 2019.

Publications

Reference-based Image Super-Resolution with Deformable Attention Transformer

European Conference on Computer Vision (ECCV) 2022
Jiezhang Cao, Jingyun Liang, Kai Zhang, Yawei Li, Yulun Zhang, Wenguan Wang, Luc Van Gool
PDF Code Slides
Reference-based Image Super-Resolution with Deformable Attention Transformer

Towards Interpretable Video Super-Resolution via Alternating Optimization

European Conference on Computer Vision (ECCV) 2022
Jiezhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, Luc Van Gool
PDF Code Slides
Towards Interpretable Video Super-Resolution via Alternating Optimization

SwinIR: Image Restoration Using Swin Transformer

IEEE International Conference on Computer Vision Workshop 2021
Jingyun Liang, Jiezhang Cao, uolei Sun, Kai Zhang, Luc Van Gool, Radu Timofte
PDF Code
SwinIR: Image Restoration Using Swin Transformer

Generative Low-bitwidth Data Free Quantization

European Conference on Computer Vision (ECCV) 2020
Shoukai Xu, Haokun Li, Bohan Zhuang, Jing Liu, Jiezhang Cao, Chuangrun Liang, Mingkui Tan
PDF Code Slides
Generative Low-bitwidth Data Free Quantization

Improving Generative Adversarial Networks with Local Coordinate Coding

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2020
Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan
PDF Code Slides
Improving Generative Adversarial Networks with Local Coordinate Coding

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020
Yong Guo, Jian Chen, Jingdong Wang, Qi Chen, Jiezhang Cao, Zeshuai Deng, Yanwu Xu, Mingkui Tan
PDF Code Slides
Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

Multi-marginal Wasserstein GAN

Neural Information Processing Systems (NeurIPS) 2019
Jiezhang Cao, Langyuan Mo, Yifan Zhang, Kui Jia, Chunhua Shen, Mingkui Tan
PDF Code Slides
Multi-marginal Wasserstein GAN

Oversampling for Imbalanced Data via Optimal Transport

AAAI Conference on Artificial Intelligence (AAAI) 2019
Yuguang Yan, Mingkui Tan, Yanwu Xu, Jiezhang Cao, Michael Kwok-Po Ng, Huaqing Min, Qingyao Wu
PDF Slides
Oversampling for Imbalanced Data via Optimal Transport

Adversarial Learning with Local Coordinate Coding

International Conference on Machine Learning (ICML) 2018
Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan
PDF Code
Adversarial Learning with Local Coordinate Coding

On the Flatness of Loss Surface for Two-layered ReLU Networks

Asian Conference on Machine Learning (ACML) 2017
Jiezhang Cao, Qingyao Wu, Yuguang Yan, Li Wang, Mingkui Tan
PDF Slides
On the Flatness of Loss Surface for Two-layered ReLU Networks

Presentations

Poster presentation of NeurIPS 2019

Multi-marginal Wasserstein GAN
Dec 10, 2019 10:45 AM — 12:45 PM Vancouver Convention Centre, Vancouver, Canada
Project Slides Follow
Poster presentation of NeurIPS 2019

Oral presentation of ICML 2018

Adversarial Learning with Local Coordinate Coding
Jul 12, 2018 2:30 AM — 2:40 AM Stockholmsmässan, Stockholm, Sweden
Project Slides Video Follow
Oral presentation of ICML 2018

Oral presentation of ACML 2017

On the Flatness of Loss Surface for Two-layered ReLU Networks
Nov 17, 2017 2:00 PM — 3:50 PM Yonsei University, Seoul, Korea
Project Slides Follow
Oral presentation of ACML 2017

Awards

Student Travel Award of NeurIPS 2019

NeurIPS Dec 2019

The First Prize Scholarship

SCUT Oct 2019

National Scholarship

Ministry of Education of China Oct 2019

Excellent Undergraduate Thesis

GDUT Jul 2017

Excellent Graduate Student

GDUT Jul 2017

Contact