Kfir Aberman

4.3k citations
32 papers · 2.0k indexed · 2 hit papers · h-index 15

Kfir Aberman

27 papers receiving 1.9k citations

Hit Papers

Null-text Inversion for Editing Real Images using Guided ...2662023202620242025250500750

Peers

Kfir Aberman
Comparison fields: 5 of 115
  • Computer Graphics and Computer-Aided Design 397
  • Computer Vision and Pattern Recognition 1.5k
  • Control and Systems Engineering 311
  • Computational Mechanics 244
  • Signal Processing 123
Replace Lvmin Zhang with:
Lvmin Zhang Hong Kong
Anyi Rao Hong Kong
Ira Kemelmacher-Shlizerman United States
Nataniel Ruiz United States
Liu Ren United States
Yuanzhen Li China
Tinghui Zhou United States
Koki Nagano United States
Haibin Huang China
Kfir Aberman relative to Lvmin Zhang Hong Kong Lvmin Zhang's profile →
Citations per field
00.5×1.5×2.1×
Lvmin Zhang · 1×
Citations per year

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

The 25 scholars most cited alongside Kfir Aberman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kfir Aberman Line = papers co-authored together Kfir Aberman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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15 202378
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About Kfir Aberman

Kfir Aberman is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Biophysics, having authored 32 papers that have together received 2.0k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (18 papers), Human Pose and Action Recognition (7 papers), Human Motion and Animation (7 papers), Computer Graphics and Visualization Techniques (6 papers), Video Analysis and Summarization (5 papers), Advanced Image Processing Techniques (5 papers), Advanced Vision and Imaging (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (397 citations), Computer Vision and Pattern Recognition (1.5k citations) and Control and Systems Engineering (311 citations). Kfir Aberman has collaborated with scholars based in United States, Israel and China. Frequent 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. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum, IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Image Processing 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.

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