Moab Arar
Impact in
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- Computer Graphics and Visualization Techniques
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- Generative Adversarial Networks and Image Synthesis
- Image Retrieval and Classification Techniques
- Video Analysis and Summarization
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
Papers in
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- Advanced Image and Video Retrieval Techniques 4
- Generative Adversarial Networks and Image Synthesis 4
- Advanced Neural Network Applications 3
- Image Retrieval and Classification Techniques 2
- Multimodal Machine Learning Applications 2
- Co-authors
- Daniel Cohen‐Or (7 shared papers)Amit Haim Bermano (5 shared papers)Yuval Atzmon (2 shared papers)Gal Chechik (2 shared papers)Rinon Gal (2 shared papers)Ariel Shamir (5 shared papers)Omri Avrahami (2 shared papers)Amir Hertz (3 shared papers)
- Journals
- ACM Transactions on Graphics (1 paper)Computational Visual Media (1 paper)Lecture notes in computer science (2 papers)DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Moab Arar
11 papers receiving 256 citations
Moab Arar's Hit Papers
Peers
Comparison fields: 5 of 50
- Computer Graphics and Computer-Aided Design 40
- Computer Vision and Pattern Recognition 191
- Media Technology 15
- Artificial Intelligence 52
- Signal Processing 17
Countries citing papers authored by Moab Arar
This map shows the geographic impact of Moab Arar'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 Moab Arar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moab Arar more than expected).
Fields of papers citing papers by Moab Arar
This network shows the impact of papers produced by Moab Arar. 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 Moab Arar. The network helps show where Moab Arar may publish in the future.
Co-authors
The 19 scholars most cited alongside Moab Arar, 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 | Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models Hit paper breakdown → | 2023 | 121 |
| 2 | 2023 | 43 | |
| 3 | 2021 | 22 | |
| 4 | 2022 | 21 | |
| 5 | 2018 | 12 | |
| 6 | 2024 | 12 | |
| 7 | 2020 | 12 | |
| 8 | 2024 | 11 | |
| 9 | 2015 | 6 | |
| 10 | 2024 | 2 | |
| 11 | 2021 | 1 |
About Moab Arar
Moab Arar is a scholar working on Computer Vision and Pattern Recognition, General Social Sciences, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Software, having authored 11 papers that have together received 263 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Generative Adversarial Networks and Image Synthesis (4 papers), Advanced Neural Network Applications (3 papers), Image Retrieval and Classification Techniques (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Multimodal Machine Learning Applications (2 papers), Computer Graphics and Visualization Techniques (1 paper) and Advanced Numerical Analysis Techniques (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (40 citations), Computer Vision and Pattern Recognition (191 citations), Media Technology (15 citations), Artificial Intelligence (52 citations) and Signal Processing (17 citations). Moab Arar has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Daniel Cohen‐Or, Amit Haim Bermano, Yuval Atzmon, Gal Chechik, Rinon Gal, Ariel Shamir, Omri Avrahami, Amir Hertz, Shiri Chechik and Clifford Stein. Their work appears in journals such as ACM Transactions on Graphics, Computational Visual Media, Lecture notes in computer science, DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.