I am a Postdoctoral Researcher at Caltech, advised by Georgia Gkioxari. I obtained my Ph.D. in Computer Science at UMass Amherst in 2023, where I was co-advised by Subhransu Maji and Daniel Sheldon. I received my Bachelor's degree at Sichuan University in China in 2015. During my undergraduate studies, I worked with Qingxiong Yang and Bin Sheng at Shanghai Jiao Tong University.
My research interests include:
Label-efficient visual understanding (self-/semi/weakly-supervised learning)
3D shape understanding, generation, and manipulation.
Applications of computer vision in other domains (e.g., ecology, chemistry, etc.)
Prospective students: Beginning in Summer 2024, I will be joining the Department of Computer Science at the University of Virginia as an Assistant Professor. I'm looking for several students to join my group. If you are interested in working with me, please email me (zezhou@caltech.edu) your CV with "Prospective student" as the subject. I'll read every email but won't be able to reply to each. Learn more about the Ph.D. program at UVa here.
2024
Gustavo Perez, Wenlong Zhao, Zezhou Cheng, Maria Carolina Belotti, Yuting Deng, Victoria Simons, Elske Tielens, Jeffrey Kelly, Kyle Horton, Subhransu Maji, Daniel Sheldon
Remote Sensing in Ecology and Conservation. 2024;
[PDF | Source code]
Keywords: AI for ecology
2023
Zezhou Cheng, Carlos Esteves, Varun Jampani, Abhishek Kar, Subhransu Maji, Ameesh Makadia
IEEE International Conference on Computer Vision (ICCV), 2023.
[PDF | Project Website]
Keywords: 3D pose estimation, Neural rendering
Zezhou Cheng, Matheus Gadelha, Subhransu Maji
ICCV workshop on Recovering 6D Object Pose (ICCV workshop), 2023.
[PDF | Project Website | Poster]
Keywords: unsupervised learning; 3D pose estimation.
Yachan Liu*, Gustavo Perez*, Zezhou Cheng, Aaron Sun, Samuel Hoover, Wei Fan, Subhransu Maji, Peng Bai (*equal contribution)
Journal of Materials Chemistry A, 2023.
[PDF | Project Website]
Keywords: 3D shape understanding; AI for Chemistry
Wenlong Zhao, Gustavo Perez, Zezhou Cheng, Maria Carolina Belotti, Yuting Deng, Victoria Simons, Elske Tielens, Jeffrey Kelly, Kyle Horton, Subhransu Maji, Daniel Sheldon
NeurIPS 2023 Computational Sustainability: Pitfalls and Promises from Theory to Deployment
[PDF | Project Website]
Keywords: AI for ecology
2022
Zezhou Cheng, Menglei Chai, Jian Ren, Hsin-Ying Lee, Kyle Olszewski, Zeng Huang, Subhransu Maji, Sergey Tulyakov
European Conference on Computer Vision (ECCV) 2022
[PDF | Source code | Project Website | Poster | Video]
Keywords: 3D shape generation and manipulation
Maria Belotti, Yuting Deng, Wenlong Zhao, Victoria Simons, Zezhou Cheng, Gustavo Perez, Elske Tielens, Subhransu Maji, Daniel Sheldon, Jeffrey Kelly, Kyle Horton
Remote Sensing in Ecology and Conservation, 2022
[PDF]
Keywords: AI for ecology
Yuting Deng, Maria Belotti, Wenlong Zhao, Zezhou Cheng, Gustavo Perez, Elske Tielens, Victoria Simons, Daniel Sheldon, Subhransu Maji, Jeff Kelly, Kyle Horton
Global Change Biology, 2022 (impact factor: 13.21)
[PDF]
Keywords: AI for ecology
Oindrila Saha, Zezhou Cheng, Subhransu Maji
European Conference on Computer Vision (ECCV) 2022
[PDF | Source code | Project Website]
Keywords: Self-/Semi-/Weakly-supervised learning
Oindrila Saha, Zezhou Cheng, Subhransu Maji
Computer Vision and Pattern Recognition (CVPR), 2022.
[PDF | Source code | Project Website]
Keywords: Self-/Semi-/Weakly-supervised learning
2021
Zezhou Cheng, Jong-Chyi Su, Subhransu Maji
IEEE International Conference on Computer Vision (ICCV), 2021.
[PDF | Source code | Project Website | arXiv | Poster | Supplementary]
Keywords: Self-/Semi-/Weakly-supervised learning
A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification
Jong-Chyi Su, Zezhou Cheng, Subhransu Maji
Computer Vision and Pattern Recognition (CVPR), 2021, (Oral).
[PDF | Source code | arXiv | Poster]
Keywords: Self-/Semi-/Weakly-supervised learning
2020
Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani, Daniel Sheldon, Subhransu Maji, Andrew Laughlin, David Winkler
Association for the Advancement of Artificial Intelligence (AAAI), 2020, (Oral)
[PDF | Source code | Project Website | arXiv | Supplementary]
Keywords: AI for ecology
2019
Zezhou Cheng, Matheus Gadelha, Subhransu Maji, Daniel Sheldon
Computer Vision and Pattern Recognition (CVPR), 2019.
[PDF | Source code | Project Website | arXiv | Poster | Supplementary ]
Keywords: Image restoration; Self-/Semi-/Weakly-supervised learning
Before 2017
Zezhou Cheng, Qingxiong Yang, and Bin Sheng
IEEE Transactions on Image Processing (TIP), 2017.
[PDF | Souce code | Project Website]
Keywords: Image restoration
Zezhou Cheng, Qingxiong Yang, and Bin Sheng
IEEE International Conference on Computer Vision (ICCV), 2015.
[PDF | Souce code | Colorized Images (view online)] (My undergraduate thesis)
Keywords: Image restoration
Working Experience
Summer 2022: Research Intern at Google Research (NYC).
Hosts: Carlos Esteves, Ameesh Makadia
Collaborators: Varun Jampani, Abhishek Kar
Summer 2021: Research Intern at Snap Research (Remote).
Hosts: Menglei Chai, Sergey Tulyakov
Collaborators: Jian Ren, Hsin-Ying Lee, Kyle Olszewski, Zeng Huan
Summer 2019: Research Intern at Amazon (Pasadena, CA.)
Host: Vijay Mahadevan
Services
Reviewer:
Conferences: NeurIPS/ ICCV / CVPR / AAAI / WACV / ICLR / ICML etc.
Journals: IJCV / TIP / TMM, etc.
Awards
Travel Award from Doctoral Consortium, CVPR 2023
Outstanding Reviewer, CVPR 2021
Outstanding Synthesis Award, UMass Amherst CICS, 2020 (top 2 synthesis)
AAAI-2020 Student Scholarship 2020
Best Poster Award at the New England Computer Vision Workshop held at Brown University 2019
UMass Amherst CICS Edward Riseman and Allen Hanson Scholarship 2018
National Scholarship, Ministry of Education, China 2016 (at Shanghai Jiao Tong University)
National Scholarship, Ministry of Education, China 2014 (at Sichuan University)
Media Coverage
Climate Change AI: Deep learning of nanoporous materials for chemical separations
UMass CICS Outstanding Synthesis: CICS Graduate Students Honored for Outstanding Synthesis Projects