Kfir Aberman

4.3k total citations · 2 hit papers
32 papers, 2.0k citations indexed

About

Kfir Aberman is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Kfir Aberman has authored 32 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 7 papers in Control and Systems Engineering and 6 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Kfir Aberman's work include Generative Adversarial Networks and Image Synthesis (18 papers), Human Pose and Action Recognition (7 papers) and Human Motion and Animation (7 papers). Kfir Aberman is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (18 papers), Human Pose and Action Recognition (7 papers) and Human Motion and Animation (7 papers). Kfir Aberman collaborates with scholars based in United States, Israel and China. Kfir Aberman's co-authors include Yael Pritch, Nataniel Ruiz, Varun Jampani, Yuanzhen Li, Michael Rubinstein, Daniel Cohen‐Or, Amir Hertz, Ron Mokady, Dani Lischinski and Baoquan Chen and has published in prestigious journals such as IEEE Transactions on Image Processing, ACM Transactions on Graphics and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Kfir Aberman

27 papers receiving 1.9k citations

Hit Papers

DreamBooth: Fine Tuning Text-to-Image Diffusion Models fo... 2023 2026 2024 2025 2023 2023 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
    2023 955 citations Nataniel Ruiz, Yuanzhen Li et al. profile →
  2. Null-text Inversion for Editing Real Images using Guided Diffusion Models
    2023 266 citations Kfir Aberman, Yael Pritch et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kfir Aberman United States 15 1.5k 397 336 311 244 32 2.0k
Lvmin Zhang Hong Kong 7 1.2k 0.8× 383 1.0× 247 0.7× 164 0.5× 210 0.9× 9 1.7k
Anyi Rao Hong Kong 9 1.2k 0.8× 316 0.8× 744 2.2× 148 0.5× 190 0.8× 19 2.1k
Yuanzhen Li China 15 1.3k 0.9× 326 0.8× 256 0.8× 128 0.4× 159 0.7× 46 1.9k
Haibin Huang China 17 1.0k 0.7× 171 0.4× 111 0.3× 250 0.8× 153 0.6× 46 1.4k
Ira Kemelmacher-Shlizerman United States 20 2.1k 1.4× 367 0.9× 176 0.5× 176 0.6× 595 2.4× 34 2.4k
Koki Nagano United States 19 1.4k 1.0× 503 1.3× 153 0.5× 104 0.3× 531 2.2× 45 1.7k
Nataniel Ruiz United States 8 842 0.6× 237 0.6× 292 0.9× 86 0.3× 139 0.6× 14 1.3k
Carl Vondrick United States 13 958 0.7× 146 0.4× 584 1.7× 103 0.3× 143 0.6× 28 1.4k
Tali Dekel Israel 16 1.1k 0.8× 246 0.6× 291 0.9× 69 0.2× 175 0.7× 32 1.6k

Countries citing papers authored by Kfir Aberman

Since Specialization
Citations

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

Fields of papers citing papers by Kfir Aberman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kfir Aberman

This figure shows the co-authorship network connecting the top 25 collaborators of Kfir Aberman. A scholar is included among the top collaborators of Kfir Aberman 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 Kfir Aberman. Kfir Aberman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Kadambi, Achuta, et al.. (2025). Personalized Restoration via Dual-Pivot Tuning. IEEE Transactions on Image Processing. 34. 5257–5270.
3.
Parmar, Gaurav, Or Patashnik, Srinivasa G. Narasimhan, et al.. (2025). Object-level Visual Prompts for Compositional Image Generation. 1–12. 1 indexed citations
4.
Patashnik, Or, et al.. (2025). Nested Attention: Semantic-aware Attention Values for Concept Personalization. 1–12. 2 indexed citations
5.
6.
Avrahami, Omri, Or Patashnik, Ohad Fried, et al.. (2025). Stable Flow: Vital Layers for Training-Free Image Editing. 7877–7888. 1 indexed citations
7.
Siarohin, Aliaksandr, Willi Menapace, Yuwei Fang, et al.. (2025). Multi-subject Open-set Personalization in Video Generation. 6099–6110. 2 indexed citations
8.
Tulyakov, Sergey, et al.. (2024). MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation. 1–12. 7 indexed citations
9.
Tang, Luming, Nataniel Ruiz, Aleksander Holynski, et al.. (2024). RealFill: Reference-Driven Generation for Authentic Image Completion. ACM Transactions on Graphics. 43(4). 1–12. 13 indexed citations
10.
Pó, Riccardo, Yifan Wang, Vladislav Golyanik, et al.. (2024). State of the Art on Diffusion Models for Visual Computing. Computer Graphics Forum. 43(2). 36 indexed citations
11.
Hanocka, Rana, et al.. (2024). TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis. Knowledge@UChicago (University of Chicago). 1–11. 6 indexed citations
12.
Yang, Guandao, et al.. (2024). Orthogonal Adaptation for Modular Customization of Diffusion Models. 7964–7973. 8 indexed citations
13.
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
14.
Voynov, Andrey, Kfir Aberman, & Daniel Cohen‐Or. (2023). Sketch-Guided Text-to-Image Diffusion Models. 1–11. 78 indexed citations
15.
Raj, Amit, Ben Poole, Michael Niemeyer, et al.. (2023). DreamBooth3D: Subject-Driven Text-to-3D Generation. 2349–2359. 87 indexed citations
16.
Aristidou, Andreas, et al.. (2022). Rhythm is a Dancer: Music-Driven Motion Synthesis With Global Structure. IEEE Transactions on Visualization and Computer Graphics. 29(8). 3519–3534. 30 indexed citations
17.
Nitzan, Yotam, Kfir Aberman, Orly Liba, et al.. (2022). MyStyle. ACM Transactions on Graphics. 41(6). 1–10. 44 indexed citations
18.
Shi, Mingyi, Kfir Aberman, Andreas Aristidou, et al.. (2020). MotioNet. ACM Transactions on Graphics. 40(1). 1–15. 63 indexed citations
19.
Aberman, Kfir, Jing Liao, Mingyi Shi, et al.. (2018). Neural best-buddies. ACM Transactions on Graphics. 37(4). 1–14. 44 indexed citations
20.
Aberman, Kfir, Qiang Zhou, Andrei Sharf, et al.. (2017). Dip transform for 3D shape reconstruction. ACM Transactions on Graphics. 36(4). 1–11. 9 indexed citations

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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