Omri Avrahami

1.3k total citations · 2 hit papers
9 papers, 694 citations indexed

About

Omri Avrahami is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Literature and Literary Theory. According to data from OpenAlex, Omri Avrahami has authored 9 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Computer Graphics and Computer-Aided Design and 1 paper in Literature and Literary Theory. Recurrent topics in Omri Avrahami's work include Generative Adversarial Networks and Image Synthesis (6 papers), Multimodal Machine Learning Applications (3 papers) and Computer Graphics and Visualization Techniques (3 papers). Omri Avrahami is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (6 papers), Multimodal Machine Learning Applications (3 papers) and Computer Graphics and Visualization Techniques (3 papers). Omri Avrahami collaborates with scholars based in Israel and United States. Omri Avrahami's co-authors include Dani Lischinski, Ohad Fried, Daniel Cohen‐Or, Kfir Aberman, Thomas Hayes, Xi Yin, Sonal Gupta, Yaniv Taigman, Devi Parikh and Oran Gafni and has published in prestigious journals such as ACM Transactions on Graphics and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Omri Avrahami

9 papers receiving 672 citations

Hit Papers

Blended Diffusion for Text-driven Editing of Natural Images 2022 2026 2023 2024 2022 2023 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Omri Avrahami Israel 6 548 169 121 78 41 9 694
Rinon Gal Israel 11 672 1.2× 170 1.0× 137 1.1× 84 1.1× 51 1.2× 20 817
Ron Mokady Israel 9 700 1.3× 174 1.0× 134 1.1× 97 1.2× 67 1.6× 10 845
Yuheng Li United States 6 502 0.9× 99 0.6× 266 2.2× 50 0.6× 37 0.9× 11 772
Yuval Alaluf Israel 11 896 1.6× 221 1.3× 154 1.3× 164 2.1× 74 1.8× 14 1.1k
Tim Brooks United States 3 376 0.7× 109 0.6× 96 0.8× 51 0.7× 41 1.0× 4 538
Kun Zeng China 10 235 0.4× 79 0.5× 96 0.8× 66 0.8× 28 0.7× 33 570
Or Patashnik Israel 9 916 1.7× 273 1.6× 155 1.3× 190 2.4× 67 1.6× 22 1.1k
Duanqing Xu China 10 582 1.1× 81 0.5× 180 1.5× 45 0.6× 67 1.6× 41 720
Toshiki Kataoka Japan 4 584 1.1× 45 0.3× 238 2.0× 36 0.5× 38 0.9× 6 740
Cengiz Öztireli Switzerland 13 461 0.8× 180 1.1× 177 1.5× 267 3.4× 19 0.5× 23 737

Countries citing papers authored by Omri Avrahami

Since Specialization
Citations

This map shows the geographic impact of Omri Avrahami'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 Omri Avrahami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Omri Avrahami more than expected).

Fields of papers citing papers by Omri Avrahami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Omri Avrahami. 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 Omri Avrahami. The network helps show where Omri Avrahami may publish in the future.

Co-authorship network of co-authors of Omri Avrahami

This figure shows the co-authorship network connecting the top 25 collaborators of Omri Avrahami. A scholar is included among the top collaborators of Omri Avrahami based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Omri Avrahami. Omri Avrahami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Avrahami, Omri, Or Patashnik, Ohad Fried, et al.. (2025). Stable Flow: Vital Layers for Training-Free Image Editing. 7877–7888. 1 indexed citations
2.
Avrahami, Omri, Rinon Gal, Gal Chechik, et al.. (2024). DiffUHaul: A Training-Free Method for Object Dragging in Images. 1–12. 5 indexed citations
3.
Avrahami, Omri, Amir Hertz, Yael Vinker, et al.. (2024). The Chosen One: Consistent Characters in Text-to-Image Diffusion Models. 1–12. 5 indexed citations
4.
Voynov, Andrey, Amir Hertz, Omri Avrahami, et al.. (2024). PALP: Prompt Aligned Personalization of Text-to-Image Models. 1–11. 7 indexed citations
5.
Avrahami, Omri, Kfir Aberman, Ohad Fried, Daniel Cohen‐Or, & Dani Lischinski. (2023). Break-A-Scene: Extracting Multiple Concepts from a Single Image. 1–12. 58 indexed citations
6.
Avrahami, Omri, Ohad Fried, & Dani Lischinski. (2023). Blended Latent Diffusion. ACM Transactions on Graphics. 42(4). 1–11. 147 indexed citations breakdown →
7.
Avrahami, Omri, Thomas Hayes, Oran Gafni, et al.. (2023). SpaText: Spatio-Textual Representation for Controllable Image Generation. 18370–18380. 77 indexed citations
8.
Avrahami, Omri, et al.. (2023). Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields. 2933–2943. 5 indexed citations
9.
Avrahami, Omri, Dani Lischinski, & Ohad Fried. (2022). Blended Diffusion for Text-driven Editing of Natural Images. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 18187–18197. 389 indexed citations breakdown →

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.

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