Eric R. Chan
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Vision and Imaging
- Generative Adversarial Networks and Image Synthesis
- Face recognition and analysis
- Advanced Image Processing Techniques
- Human Pose and Action Recognition
Papers in
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- Advanced Vision and Imaging 6
- Graph Theory and Algorithms 1
- Image Processing and 3D Reconstruction 1
- Generative Adversarial Networks and Image Synthesis 1
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- Computer Graphics and Visualization Techniques 6
- Co-authors
- Gordon Wetzstein (6 shared papers)Connor Z. Lin (3 shared papers)Koki Nagano (3 shared papers)Matthew A. Chan (2 shared papers)Shalini De Mello (2 shared papers)Tero Karras (2 shared papers)Sameh Khamis (2 shared papers)Leonidas Guibas (1 shared paper)
- Journals
- ACM Transactions on Graphics (3 papers)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United States
In The Last Decade
Eric R. Chan
8 papers receiving 839 citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Computer Graphics and Computer-Aided Design 410
- Computer Vision and Pattern Recognition 677
- Computational Mechanics 376
- Geology 40
- Media Technology 30
Countries citing papers authored by Eric R. Chan
This map shows the geographic impact of Eric R. Chan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eric R. Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric R. Chan more than expected).
Fields of papers citing papers by Eric R. Chan
This network shows the impact of papers produced by Eric R. Chan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eric R. Chan. The network helps show where Eric R. Chan may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric R. Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Efficient Geometry-aware 3D Generative Adversarial Networks Hit paper breakdown → | 2022 | 600 |
| 2 | 2021 | 111 | |
| 3 | 2023 | 66 | |
| 4 | 2023 | 32 | |
| 5 | 2002 | 24 | |
| 6 | 2024 | 13 | |
| 7 | MetaSDF: Meta-Learning Signed Distance Functions | 2020 | 9 |
| 8 | 2021 | 3 |
About Eric R. Chan
Eric R. Chan is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computational Mechanics, Hardware and Architecture and Biophysics, having authored 8 papers that have together received 858 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (6 papers), Advanced Vision and Imaging (6 papers), 3D Shape Modeling and Analysis (4 papers), Graph Theory and Algorithms (1 paper), Parallel Computing and Optimization Techniques (1 paper), Cell Image Analysis Techniques (1 paper), Image Processing and 3D Reconstruction (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (410 citations), Computer Vision and Pattern Recognition (677 citations), Computational Mechanics (376 citations), Geology (40 citations) and Media Technology (30 citations). Eric R. Chan has collaborated with scholars based in United States. Frequent co-authors include Gordon Wetzstein, Connor Z. Lin, Koki Nagano, Matthew A. Chan, Shalini De Mello, Tero Karras, Sameh Khamis, Leonidas Guibas, Orazio Gallo and Boxiao Pan. Their work appears in journals such as ACM Transactions on Graphics, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.