Hao Zhou

I am a software enginner at Google Research where I work on computer vision and machine learning.

Bio: I obtained my PhD at Department of Computer Science, University of Maryland, College Park supervied by Prof. David W. Jacobs in 2019. Before that, I received an M.Phil. from the University of Hong Kong under supervision of Dr. Kenneth K.Y. Wong in 2012, and a B.Eng in the University of Science and Technology of China in 2010.

During my PhD studies, I was lucky to join Adobe Research, NEC Labs America and National ICT (NICTA) Australia as a research intern.

Before joining Google Research, I worked as an applied scientist in AWS Rekognition.

Email / CV / Google Scholar / Github

Research

Much of my current work is about image/video understanding. During my PhD stuides, my research is mainly about understanding lighting from images. Some selected papers are listed below. For a full list of papers, refer to my Google Scholar.

	VideoGLUE: Video General Understanding Evaluation of Foundation Models. Liangzhe Yuan, Nitesh Bharadwaj Gundavarapu, Long Zhao, Hao Zhou, Yin Cui, Lu Jiang, Xuan Yang, Menglin Jia, Tobias Weyand, Luke Friedman, Mikhail Sirotenko, Huisheng Wang, Florian Schroff, Hartwig Adam, Ming-Hsuan Yang, Ting Liu and Boqing Gong. Arxiv, 2023. Paper
	Towards Regression-Free Neural Networks for Diverse Compute Platforms. Rahul Duggal, Hao Zhou, Shuo Yang, Jun Fang, Yuanjun Xiong and Wei Xia. ECCV, 2022. Paper
	PSS: Progressive Sample Selection for Open-World Visual Representation Learning Tianyue Cao, Yongxin Wang, Yifan Xing, Tianjun Xiao, Tong He, Zheng Zhang, Hao Zhou, and Joseph Tighe. ECCV, 2022. Paper / Code

Compatibility-aware Heterogeneous Visual Search.
Rahul Duggal, Hao Zhou, Shuo Yang, Yuanjun Xiong, Wei Xia, Zhuowen Tu, Stefano Soatto.
CVPR, 2021.
Paper

Mentioned by the VP of AWS AI in Graceful AI

SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation.
Koutilya PNVR, Hao Zhou, David Jacobs.
CVPR, 2020.
Paper / Code

Deep Single-Image Portrait Relighting.
Hao Zhou, Sunil Hadap, Kalyan Sunkavalli and David W. Jacobs
ICCV, 2019.
Paper / Code / Project

Covered by Two Minutes Paper

GLoSH: Global-Local Spherical Harmonics for Intrinsic Image Decomposition.
Hao Zhou, Xiang Yu and David W. Jacobs
ICCV, 2019. (Oral Presentation)
Paper

Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Faces.
Hao Zhou, Jin Sun, Yaser Yacoob and David W. Jacobs
CVPR, 2018. (Spotlight)
Paper

Solving Uncalibrated Photometric Stereo Using Fewer Images by Jointly Optimizing Low-rank Matrix Completion and Integrability.
Soumyadip Sengupta, Hao Zhou, Walter Forkel, Ronen Basri, Tom Goldstein, David W Jacobs.
JMIV, 2017.
Paper

Less is More: Towards Compact CNNs.
Hao Zhou, Jose M. Alvarez and Fatih Porikli.
ECCV, 2016. (Spotlight)
Paper

Evaluating Local Features for Day-Night Matching.
Hao Zhou, Torsten Sattler and Fatih Porikli.
ECCV Workshop on Local Features: State of the Art, Open Problems and Performance Analysis, 2016.
Paper

Markov Weight Fields for Face Sketch Synthesis.
Hao Zhou, Zhanghui Kuang and Kwan-Yee K. Wong.
CVPR, 2012.
Paper

The portrait is drawn by Daichi Ito when I interned in Adobe.

This website is designed according to the website of Jon Barron.