Eli Shechtman

39.7k total citations · 14 hit papers
120 papers, 13.4k citations indexed

About

Eli Shechtman is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence. According to data from OpenAlex, Eli Shechtman has authored 120 papers receiving a total of 13.4k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Computer Vision and Pattern Recognition, 32 papers in Computer Graphics and Computer-Aided Design and 10 papers in Artificial Intelligence. Recurrent topics in Eli Shechtman's work include Advanced Vision and Imaging (60 papers), Generative Adversarial Networks and Image Synthesis (44 papers) and Advanced Image and Video Retrieval Techniques (34 papers). Eli Shechtman is often cited by papers focused on Advanced Vision and Imaging (60 papers), Generative Adversarial Networks and Image Synthesis (44 papers) and Advanced Image and Video Retrieval Techniques (34 papers). Eli Shechtman collaborates with scholars based in United States, Israel and Czechia. Eli Shechtman's co-authors include Michal Irani, Dan B Goldman, M. Irani, Connelly Barnes, Adam Finkelstein, Ronen Basri, Miri Blank, Lena Gorelick, Yonatan Wexler and Dani Lischinski and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM and ACM Transactions on Graphics.

In The Last Decade

Eli Shechtman

117 papers receiving 13.0k citations

Hit Papers

PatchMatch 2005 2026 2012 2019 2009 2005 2007 2008 2007 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eli Shechtman United States 47 12.3k 2.0k 1.8k 1.2k 1.0k 120 13.4k
Ronen Basri Israel 37 7.0k 0.6× 1.5k 0.8× 748 0.4× 714 0.6× 1.1k 1.1× 111 8.7k
Jan Kautz United Kingdom 61 13.4k 1.1× 2.2k 1.1× 4.1k 2.2× 2.4k 1.9× 2.4k 2.3× 234 17.2k
Carsten Rother United Kingdom 60 13.7k 1.1× 1.7k 0.8× 929 0.5× 2.0k 1.7× 825 0.8× 141 16.5k
Shi‐Min Hu China 55 11.3k 0.9× 1.1k 0.5× 2.6k 1.4× 1.6k 1.3× 3.2k 3.1× 293 15.6k
Patrick Pérez France 26 8.5k 0.7× 857 0.4× 1.6k 0.8× 987 0.8× 985 1.0× 78 9.7k
Ming-Yu Liu United States 26 6.4k 0.5× 1.2k 0.6× 982 0.5× 1.2k 0.9× 711 0.7× 73 8.2k
Lu Yuan China 49 8.4k 0.7× 1.7k 0.8× 727 0.4× 1.9k 1.5× 433 0.4× 107 10.4k
Jiwen Lu China 71 13.7k 1.1× 3.3k 1.6× 541 0.3× 1.4k 1.1× 1.6k 1.6× 387 16.7k
Aaron Hertzmann United States 53 10.1k 0.8× 1.1k 0.5× 3.3k 1.8× 1.3k 1.1× 2.7k 2.7× 139 13.1k
Fisher Yu United States 32 7.8k 0.6× 2.6k 1.3× 893 0.5× 855 0.7× 2.0k 2.0× 70 11.1k

Countries citing papers authored by Eli Shechtman

Since Specialization
Citations

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

Fields of papers citing papers by Eli Shechtman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eli Shechtman

This figure shows the co-authorship network connecting the top 25 collaborators of Eli Shechtman. A scholar is included among the top collaborators of Eli Shechtman 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 Eli Shechtman. Eli Shechtman 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.
Xia, Zhihao, et al.. (2025). Magic Fixup: Streamlining Photo Editing by Watching Dynamic Videos. ACM Transactions on Graphics. 44(5). 1–25. 3 indexed citations
2.
Chen, Yinbo, Oliver Wang, Richard Zhang, et al.. (2024). Image Neural Field Diffusion Models. 8007–8017.
3.
Kang, Minguk, Jun-Yan Zhu, Richard Zhang, et al.. (2023). Scaling up GANs for Text-to-Image Synthesis. 10124–10134. 186 indexed citations breakdown →
4.
Or-El, Roy, et al.. (2022). StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 13493–13503. 164 indexed citations breakdown →
5.
Park, Taesung, Jun-Yan Zhu, Oliver Wang, et al.. (2020). Swapping Autoencoder for Deep Image Manipulation. Neural Information Processing Systems. 33. 7198–7211. 13 indexed citations
6.
Shechtman, Eli, et al.. (2019). Saliency driven image manipulation. Machine Vision and Applications. 30(2). 189–202. 26 indexed citations
7.
Fišer, Jakub, et al.. (2019). 例によるビデオのスタイリング【JST・京大機械翻訳】. ACM Transactions on Graphics. 38(4). 1–11. 1 indexed citations
8.
Jamriška, Ondřej, Michal Lukáč, Jakub Fišer, et al.. (2019). Stylizing video by example. ACM Transactions on Graphics. 38(4). 1–11. 55 indexed citations
9.
Hendricks, Lisa Anne, Oliver Wang, Eli Shechtman, et al.. (2018). Localizing Moments in Video with Temporal Language. arXiv (Cornell University). 1380–1390. 71 indexed citations
10.
Hendricks, Lisa Anne, Oliver Wang, Eli Shechtman, et al.. (2017). Localizing Moments in Video with Natural Language. arXiv (Cornell University). 5804–5813. 39 indexed citations
11.
Zhu, Jun, Richard Zhang, Deepak Pathak, et al.. (2017). Toward Multimodal Image-to-Image Translation. arXiv (Cornell University). 30. 465–476. 203 indexed citations
12.
Zhu, Jun-Yan, Richard Zhang, Deepak Pathak, et al.. (2017). Multimodal Image-to-Image Translation by Enforcing Bi-Cycle Consistency. Neural Information Processing Systems. 465–476. 20 indexed citations
13.
Gatys, Leon A., Alexander S. Ecker, Matthias Bethge, Aaron Hertzmann, & Eli Shechtman. (2017). Controlling Perceptual Factors in Neural Style Transfer. 3730–3738. 276 indexed citations
14.
Yan, Shuicheng, Hailin Jin, Eli Shechtman, et al.. (2015). Real-world font recognition using deep network and domain adaptation. International Conference on Learning Representations. 1 indexed citations
15.
Chen, Guang, et al.. (2015). Selective Pooling Vector for Fine-Grained Recognition. 860–867. 18 indexed citations
16.
Jamriška, Ondřej, Jakub Fišer, Paul Asente, et al.. (2015). LazyFluids. ACM Transactions on Graphics. 34(4). 1–10. 39 indexed citations
17.
Yang, Fei, Eli Shechtman, Jue Wang, Lubomir Bourdev, & Dimitris Metaxas. (2012). Face morphing using 3D-aware appearance optimization. Graphics Interface. 93–99. 16 indexed citations
18.
Barnes, Connelly, Dan B Goldman, Eli Shechtman, & Adam Finkelstein. (2010). Video tapestries with continuous temporal zoom. ACM Transactions on Graphics. 29(4). 1–9. 59 indexed citations
19.
Wexler, Yonatan, Eli Shechtman, & Michal Irani. (2007). Space-Time Completion of Video. IEEE Transactions on Pattern Analysis and Machine Intelligence. 29(3). 463–476. 481 indexed citations breakdown →
20.
Gorelick, Lena, Miri Blank, Eli Shechtman, M. Irani, & Ronen Basri. (2007). Actions as Space-Time Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 29(12). 2247–2253. 976 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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