Marc Szafraniec

1.1k total citations
2 papers, 3 citations indexed

About

Marc Szafraniec is a scholar working on Computer Vision and Pattern Recognition, Infectious Diseases and Organic Chemistry. According to data from OpenAlex, Marc Szafraniec has authored 2 papers receiving a total of 3 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Computer Vision and Pattern Recognition, 0 papers in Infectious Diseases and 0 papers in Organic Chemistry. Recurrent topics in Marc Szafraniec's work include Multimodal Machine Learning Applications (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Image Retrieval and Classification Techniques (1 paper). Marc Szafraniec is often cited by papers focused on Multimodal Machine Learning Applications (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Image Retrieval and Classification Techniques (1 paper). Marc Szafraniec collaborates with scholars based in United Kingdom and Israel. Marc Szafraniec's co-authors include David Novotný, Huy V. Vo, Natalia Neverova, Vasil Khalidov, Timothée Darcet, Cijo Jose, Maxime Oquab, Andrea Vedaldi, Hu Xu and Oriane Siméoni and has published in prestigious journals such as arXiv (Cornell University).

In The Last Decade

Marc Szafraniec

2 papers receiving 3 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marc Szafraniec United Kingdom	2	3	2	1	1	1	2	3
Luca Moschella Italy	2	3 1.0×	2 1.0×				2	5
J. Hu China	2	3 1.0×	2 1.0×				7	4
Tuomas Kynkäänniemi Finland	2	2 0.7×	2 1.0×				3	5
Pratik Kayal India	1	3 1.0×					2	3
X.L. Li China	2	3 1.0×				1 1.0×	3	6
Cecelia Jankowski United States	2	3 1.0×			1 1.0×		2	7
Ruiqi Li China	2	3 1.0×					3	4
Yatian Pang Singapore	2	3 1.0×	1 0.5×				5	4
Y. Lu China	2	3 1.0×					4	4
H. S. Chen China	2	3 1.0×		1 1.0×			3	10

Countries citing papers authored by Marc Szafraniec

Since Specialization

Citations

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

Fields of papers citing papers by Marc Szafraniec

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marc Szafraniec

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

All Works

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2 of 2 papers shown

1.

Jose, Cijo, Théo Moutakanni, Timothée Darcet, et al.. (2025). DINOv2 Meets Text: A Unified Framework for Image- and Pixel-Level Vision-Language Alignment. 24905–24916. 1 indexed citations

2.

Neverova, Natalia, David Novotný, Vasil Khalidov, et al.. (2020). Continuous Surface Embeddings. arXiv (Cornell University). 33. 17258–17270. 2 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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