Sicheng Gao

I am a PhD student at Julius-Maximilians-Universität of Würzburg (JMU), supervised by Prof. Radu Timofte. My research focuses on Computer Vision and Machine Learning, including Image and Video Super-Resolution, Generative Models, 3D Scene Rendering, and Model Compression. Earlier I completed my M.Eng. at Beihang University, where I worked with Prof. Baochang Zhang and Prof. Jianzhuang Liu.

Email / CV / Github

Experience

PhD student in Computer Vision, Julius-Maximilians-Universität of Würzburg, Mar. 2024 - Present

Research Intern, NUS CVML Group, Jun. 2023 - Nov. 2023

Research Intern, United Imaging Intelligence, Nov. 2022 - May. 2023

M.Eng. in Pattern Recognition and Intelligent Systems, Beihang University, Sep. 2021 - Dec. 2023

Research Intern, SenseTime Research, Jan. 2021 - Jul. 2021

B.Eng. in Agricultural Mechanization and Automation, China Agricultural University, Sep. 2017 - Jun. 2021

Research

	Implicit Diffusion Models for Continuous Super-Resolution Sicheng Gao, Xuhui Liu, Bohan Zeng, Sheng Xu, Yanjing Li, Xiaoyan Luo, Jianzhuang Liu, Xiantong Zhen, Baochang Zhang CVPR*, 2023 paper / code When diffusion models meet implicit neural representations.
	MagFormer: Hybrid Video Motion Magnification Transformer from Eulerian and Lagrangian Perspectives Sicheng Gao, Yutang Feng, Linlin Yang, Xuhui Liu, Zichen Zhu, David Doermann, Baochang Zhang BMVC, 2022 paper A inspiration from fluid mechanics.
	Face Animation with an Attribute-Guided Diffusion Model Bohan Zeng, Xuhui Liu, Sicheng Gao*, Hong Li, Boyu Liu, Yanjing Li, Jianzhuang Liu, Xiantong Zhen, Baochang Zhang CVPR Workshop 2023 paper / code The first face animation method by diffusion models.
	Controllable Mind Visual Diffusion Model Bohan Zeng, Shanglin Li, Xuhui Liu, Sicheng Gao, Jianzhuang Liu, Baochang Zhang AAAI 2024 paper / code

The website template is borrowed from here.