Matan Atzmon
Impact in
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- Computer Graphics and Visualization Techniques
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- 3D Surveying and Cultural Heritage
Papers in
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- Advanced Vision and Imaging 2
- Advanced Neural Network Applications 1
- Human Pose and Action Recognition 1
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- 3D Shape Modeling and Analysis 4
- Advanced Numerical Analysis Techniques 1
- Co-authors
- Sanja Fidler (2 shared papers)Jiahui Huang (1 shared paper)Or Litany (1 shared paper)Žan Gojčič (1 shared paper)FRANCIS H. WILLIAMS (1 shared paper)Lior Yariv (3 shared papers)Yaron Lipman (4 shared papers)Ronen Basri (1 shared paper)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)arXiv (Cornell University) (2 papers)
In The Last Decade
Matan Atzmon
5 papers receiving 55 citations
Peers
Comparison fields: 5 of 20
- Computer Graphics and Computer-Aided Design 30
- Geology 12
- Computational Mechanics 37
- Computer Vision and Pattern Recognition 22
- Instrumentation 3
Countries citing papers authored by Matan Atzmon
This map shows the geographic impact of Matan Atzmon'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 Matan Atzmon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matan Atzmon more than expected).
Fields of papers citing papers by Matan Atzmon
This network shows the impact of papers produced by Matan Atzmon. 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 Matan Atzmon. The network helps show where Matan Atzmon may publish in the future.
Co-authors
The 14 scholars most cited alongside Matan Atzmon, 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 | 2023 | 38 | |
| 2 | Multiview Neural Surface Reconstruction with Implicit Lighting and Material | 2020 | 6 |
| 3 | Controlling Neural Level Sets | 2019 | 5 |
| 4 | 2022 | 4 | |
| 5 | Universal Differentiable Renderer for Implicit Neural Representations. | 2020 | 3 |
About Matan Atzmon
Matan Atzmon is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Materials Chemistry, having authored 5 papers that have together received 56 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (4 papers), Computer Graphics and Visualization Techniques (3 papers), Advanced Vision and Imaging (2 papers), Adversarial Robustness in Machine Learning (1 paper), Machine Learning in Materials Science (1 paper), Advanced Neural Network Applications (1 paper), Advanced Numerical Analysis Techniques (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (30 citations), Geology (12 citations), Computational Mechanics (37 citations), Computer Vision and Pattern Recognition (22 citations) and Instrumentation (3 citations). Matan Atzmon has collaborated with scholars based in Israel and Canada. Frequent co-authors include Sanja Fidler, Jiahui Huang, Or Litany, Žan Gojčič, FRANCIS H. WILLIAMS, Lior Yariv, Yaron Lipman, Ronen Basri, Dror Moran and Haggai Maron. Their work appears in journals such as 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.