About Me

I am a research scientist at Huawei and lead a creative team. Previously, I was a post-doctoral researcher at Max Planck Institute for Informatics, working closely with Prof. Bernt Schiele. Before that, I obtained my PhD degree from South China University of Technology, supervised by Prof. Jian Chen and Prof. Mingkui Tan. My research interests include machine learning and computer vision.

Research Interests

  • AIGC Efficient Foundation Models
  • Model Compression
  • Image/Video Restoration
[Hiring!] Actively recruiting research interns, scientists, and engineers, who would like to work in Shanghai. Please feel free to contact me!

Recent News

  • 2026/02    One paper is accepted by TMM 2026.
  • 2026/01    Two papers are accepted by ICLR 2026.
  • 2025/11    Two papers are accepted by TIP in 2025.
  • 2025/11    Three papers are accepted by AAAI 2026.
  • 2025/09    Five papers are accepted by NeurIPS 2025.
  • 2025/06    Two papers are accepted by ICCV 2025.
  • 2025/05    Two papers are accepted by ICML 2025.
  • 2025/02    Four papers are accepted by CVPR 2025.

Selected Publications

[Full List]

Conference Paper

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

Accepted by CVPR, 2020
Yong Guo, Jian Chen, Jingdong Wang, Qi Chen, Jiezhang Cao, Zeshuai Deng, Yanwu Xu, Mingkui Tan
PDF Code Poster Slides

NAT: Neural Architecture Transformer for Accurate and Compact Architectures

Accepted by NeurIPS, 2019
Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang
PDF Code Poster Slides

MambaIRv2: Attentive State Space Restoration

Accepted by CVPR, 2025
Hang Guo*, Yong Guo*, Yaohua Zha, Yulun Zhang, Wenbo Li, Tao Dai, Shu-Tao Xia, Yawei Li
PDF Code

Discrimination-aware Channel Pruning for Deep Neural Networks

Accepted by NeurIPS, 2018
Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, Jinhui Zhu
PDF Code

Robustifying Token Attention for Vision Transformers

Accepted by ICCV, 2023
Yong Guo, David Stutz, Bernt Schiele
PDF Code

Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search

Accepted by ICML, 2020
Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan
PDF Code Poster Slides

Contrastive Neural Architecture Search with Neural Architecture Comparators

Accepted by CVPR, 2021 $~~~~$(co-first author)
Yaofo Chen$^*$, Yong Guo$^*$, Qi Chen, Minli Li, Yaowei Wang, Wei Zeng, Mingkui Tan
PDF Code

Journal Paper

Towards Accurate and Compact Architectures via Neural Architecture Transformer

Accepted by TPAMI, 2021
Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang
PDF Code

Towards Lightweight Super-Resolution with Dual Regression Learning

Accepted by TPAMI, 2024
Yong Guo, Mingkui Tan, Zeshuai Deng, Jingdong Wang, Qi Chen, Jiezhang Cao, Yanwu Xu, Jian Chen
PDF Code

Discrimination-aware Network Pruning for Deep Model Compression

Accepted by TPAMI, 2021
Jing Liu, Bohan Zhuang, Zhuangwei Zhuang, Yong Guo, Junzhou Huang, Jinhui Zhu, Mingkui Tan
PDF Code

Improving Generative Adversarial Networks with Local Coordinate Coding

Accepted by TPAMI, 2020 $~~~~$(co-first author)
Jiezhang Cao$^*$, Yong Guo$^*$, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan
PDF Code

DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model

Accepted by IEEE Robotics and Automation Letters, 2024
Zhenhua Xu, Yujia Zhang, Enze Xie, Zhen Zhao, Yong Guo, Kwan-Yee K. Wong, Zhenguo Li, Hengshuang Zhao
PDF Code

Enhanced Long-Tailed Recognition with Contrastive CutMix Augmentation

Accepted by TIP, 2024
Haolin Pan$^*$, Yong Guo$^*$, Mianjie Yu, Jian Chen
Code

Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis

Accepted by TMM, 2019
Yong Guo, Qi Chen, Jian Chen, Qingyao Wu, Qinfeng Shi, Mingkui Tan
PDF Code

Honor & Award

  • Assistant Chief Scientist at Huawei, 2024
  • MSRA Fellowship Nomination Award, 2018
  • Oral Presentation at ECCV in Tel Aviv, 2022
  • Oral Presentation at ICML in Stockholm, 2018
  • Oral Presentation at AAAI in New Orleans, 2018
  • National Scholarship, 2019 & 2020
  • Principle's Scholarship of SCUT, 2019 & 2020
  • Excellent Doctoral Innovation Fund of SCUT, 2019
  • Excellent Papers of Computer Academy of Guangdong (First Prize), 2021
  • Excellent Degree Dissertations of SCUT (Bachelor Degree), 2016

Internship & Collaboration

I am looking for self-motivated intern students that have an interest in my research areas. There is always room for new ideas and projects and I am happy to discuss them with you. When you are highly motivated, please send your CV to my email guoyongcs@gmail.com.

What you can get as an intern:

  • In-depth guidance towards publishing papers in top-tier conferences/journals
  • Sufficient computational resources
  • Competitive internship salary