Zhichao Yin

I'm graduating from Carnegie Mellon University in December 2020. My research interests revolve around computer vision and mobile photography, including geometry understanding and motion analysis of general images or videos.

In summer 2020, I'm fortunate to work with Tianfan Xue and Rahul Garg at Google Research. Prior to that, I was a full-time researcher at Berkeley DeepDrive, where I collaborated with Fisher Yu. I have also worked with Jianping Shi. I did my bachelors in Mathematics at Fudan University.

E-mail  /  Google Scholar  /  Github  /  LinkedIn

Research
HD3

Hierarchical Discrete Distribution Decomposition for Match Density Estimation
Zhichao Yin, Trevor Darrell, Fisher Yu
Computer Vision and Pattern Recognition (CVPR), 2019

Paper  /  Code  /  Bibtex
@inproceedings{yin2019hd3,
title = {Hierarchical Discrete Distribution Decomposition
for Match Density Estimation},
author = {Yin, Zhichao and Darrell, Trevor and Yu,
Fisher},
booktitle = {CVPR},
year = {2019}
}
                  

We propose Hierarchical Discrete Distribution Decomposition (HD3), a framework suitable for learning probabilistic pixel correspondences. Our method achieves state-of-the-art results on both KITTI Stereo & Flow Benchmarks (ranked the 1st in optical flow).

GeoNet

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose
Zhichao Yin, Jianping Shi
Computer Vision and Pattern Recognition (CVPR), 2018

Paper  /  Code  /  Bibtex
@inproceedings{yin2018geonet,
  title     = {GeoNet: Unsupervised Learning of Dense Depth,
              Optical Flow and Camera Pose},
  author    = {Yin, Zhichao and Shi, Jianping},
  booktitle = {CVPR},
  year = {2018}
}
                  

We propose GeoNet, a jointly unsupervised learning framework for monocular depth, optical flow and ego-motion estimation from videos.

Services

Journal Reviewer for TPAMI, TIP, TCSVT, TCI
Conference Reviewer for CVPR, ICCV, ECCV, AAAI, ICRA, IROS, WACV


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