About

I am currently a Ph.D. student at the Department of Automation, University of Science and Technology of China (USTC), advised by Prof. Feng Zhao at BIVLab. I obtained my Bachelor degree in the School of Electronic Engineering, XiDian University (XDU) in 2021. My current research include reasoning in large language models and Reinforcement Learning, and I previously worked in computer vision, especially generative models and low-level vision tasks.

Address

University of Science and Technology of China, Anhui, 230031, China.

jhaozhang@mail.ustc.edu.cn and hao74531@gmail.com

Selected Publications

Jinghao Zhang, Wen Qian, Hao Luo, Fan Wang, and Feng Zhao. AnyLogo: Symbiotic Subject-Driven Diffusion System with Gemini Status. Arxiv, 2024.
[PDF] [Project Page]

Jinghao Zhang, Zizheng Yang, Qi Zhu, and Feng Zhao. Prototype Clustered Diffusion Models for Versatile Inverse Problems. Arxiv, 2024.
[PDF] [Project Page]

Jinghao Zhang, and Feng Zhao. Decomposition Ascribed Synergistic Learning for Unified Image Restoration. Arxiv, 2023.
[PDF] [Project Page]

Jinghao Zhang, Jie Huang, Mingde Yao, Zizheng Yang, Hu Yu, Man Zhou, and Feng Zhao. Ingredient-oriented Multi-Degradation Learning for Image Restoration. In IEEE Conference on Computer Vision and Pattern Recognition, 2023 (CVPR).
[PDF] [Project Page]

Jie Huang, Man Zhou, Jinghao Zhang, Gang Yang, Mingde Yao, Chongyi Li, Zhiwei Xiong, and Feng Zhao. Transition-constant Normalization for Image Enhancement. Advances in Neural Information Processing Systems, 2023 (NeurIPS).
[PDF] [Project Page]

Zizheng Yang, Jie Huang, Jiahao Chang, Man Zhou, Hu Yu, Jinghao Zhang, Feng Zhao. Visual Recognition-Driven Image Restoration for Multiple Degradation with Intrinsic Semantics Recovery. In IEEE Conference on Computer Vision and Pattern Recognition, 2023 (CVPR).
[PDF] [Project Page]

Jie Huang, Yajing Liu, Feng Zhao, Keyu Yan, Jinghao Zhang, Yukun Huang, Man Zhou, and Zhiwei Xiong. Deep Fourier- based Exposure Correction Network with Spatial-Frequency Interaction. In European Conference on Computer Vision, 2022 (ECCV, Oral).
[PDF] [Project Page]

Jinghao Zhang, Jie Huang, Mingde Yao, Man Zhou, and Feng Zhao. Structure- and Texture-Aware Learning for Low-Light Image Enhancement. In ACM International Conference on Multimedia, 2022 (ACM MM).
[PDF] [Project Page]