Han Yi

Hello! I am currently a first-year CS PhD student at the University of North Carolina at Chapel Hill (UNC), under the guidance of Prof. Gedas Bertasius. I completed my Master's degree at the National University of Singapore (NUS) in 2024. During my time at NUS, I also served as a research intern at the NExT++ Research Center, where I was advised by Prof. Tat-Seng Chua, Prof. Zhedong Zheng, and Prof. Xiangyu Xu.

I love basketball, football, rap music, and fitness.

Email / CV / Google Scholar / Github

Research

I am passionate about advancing the field of deep learning and computer vision, with a particular emphasis on Neural Radiance Fields (NeRF), 3D generation, and video synthesis. My research is dedicated to exploring innovative methods for generating high-quality, controllable 3D and video content, with a special focus on applications in sports analytics, particularly in controlled basketball video generation.

	Progressive Text-to-3D Generation for Automatic 3D Prototyping Han Yi, Zhedong Zheng, Xiangyu Xu, Tat-seng Chua arXiv, 2023 A progressive strategy that learns text-to-3D in a coarse-to-fine manner.
	Image Deblurring With Image Blurring Ziyao Li, Zhi Gao, Han Yi, Yu Fu, Boan Chen IEEE Transactions on Image Processing (TIP), 2023 Proposed a novel motion deblurring framework using Blur Space Disentangled Network (BSDNet) and Hierarchical Scale-recurrent Deblurring Network (HSDNet) to effectively address real-world blur, achieving state-of-the-art results.
	Single image deraindrop leveraging luminance priors and context aggregation Yi Liu, Zhi Gao, Tiancan Mei, Han Yi Neurocomputing, 2024 Developed a recurrent single-image deraindrop approach utilizing luminance priors and contextual feature aggregation, achieving superior performance in restoring color and texture consistency.

Services

Reviewer: ACM MM 2024, ICLR 2025

This webpage is adapted from Jon Barron's page.