Shi Mao

I am currently pursuing my Ph.D. in Computer Science at the Visual Computing Center at King Abdullah University of Science and Technology (KAUST). I works under the guidance of Prof. Wolfgang Heidrich as a member of the Computational Imaging Group.

I got my M.S. degree from Tsinghua-Berkely Shenzhen Institute (TBSI), Tsinghua University, where I was co-advised by Prof. Qionghai Dai and Prof. Lu Fang. Before that, I received my B.E. degree from South China University of Technology (SCUT), where I studied intelligence science and technology. I had a wonderful time in UC Berkely as a visiting student during my senior year and serves a research consultant at Baidu Research before joining KAUST.

My research interest spans computational imaging and 3D vision.

Email / CV / Bio / Google Scholar / Github

Research

	Generating Material-Aware 3D Models from Sparse Views S. Mao, C. Wu, R. Yi, Z. Shen, L. Zhang, W. Heidrich IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR) Workshop PBDL , 2024 bibtex / paper / code an Inverse rendering pipeline incorporates Pre-Integrated Rendering and Neural Surface Representation to learn high-quality geometry with all-frequency illumination..
	NeuS-PIR: Learning Relightable Neural Surface using Pre-Integrated Rendering S. Mao, C. Wu, Z. Shen, Y. Wang, D. Wu, L. Zhang arXiv, 2023 bibtex / paper / code an Inverse rendering pipeline incorporates Pre-Integrated Rendering and Neural Surface Representation to learn high-quality geometry with all-frequency illumination..
	Surface Material Perception Through Multimodal Learning S. Mao, M. Ji, B. Wang, Q. Dai, and L. Fang IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2022 bibtex / paper / code Material's subsurface scattering feature can be probed by dot-pattern illumination emitted by the structured ligh camera. By fusing with reflection and texture features, the material recognition power is enhanced.
	GigaMVS: A Benchmark for Ultra-large-scale Gigapixel-level 3D Reconstruction J. Zhang, J. Zhang, S. Mao, M. Ji, G. Wang, Z. Chen, T. Zhang, X. Yuan, Q. Dai, and L. Fang IEEE trans. on Pattern Analysis and Machine Intelligence (TPAMI)*, 2021 website / bibtex / paper We build a high-resolution MVS benchmark to support large-scale 3D reconstruction with fine details.
	CNN and PCA based visual system of a wheelchair manipulator robot for automatic drinking Z. Zhang, S. Mao, K. Chen, L. Xiao, B. Liao, C. Li, P. Zhang IEEE International Conference on Robotics and Biomimetics (ROBIO), 2018 Recognize and localize the cup for grasping by computer vision, after decoding the patient's intention by EEG.

Education

		Fall 2023 - Ph.D. in Computer Science Visual Computing Center, King Abdullah University of Science and Technology (KAUST) advised by Prof. Wolfgang Heidrich
		Fall 2019 - Spring 2022 M. S. in Data Science and Technology Tsinghua-Berkely Shenzhen Institute (TBSI), Tsinghua University (THU) co-advised by Prof. Qionghai Dai and Prof. Lu Fang GPA: 3.95 Rank:2/98
		Fall 2015 - Spring 2019 B. E. in Intelligence Science and Technology Department of Automation, South China University of Technology (SCUT) Chinese National Scholarship, by Minister of Education of China, 2017 Chinese National Scholarship, by Minister of Education of China, 2016 GPA: 3.90 Rank:1/50
		Fall 2018 Visiting Student in Computer Science and Statistics Exchange Program, University of California, Berkely (UCB) Coursework: Introduction to Artificial Intelligence (CS 188, A), High-Dimensional Data Analysis with Low-Dimensional Models (EE290T, B+), Probability for Data Science (Prob 140, A+), Special Topics on Deep Learning (CS294-131, A)

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