Face2Face: Real-Time Face Capture and Reenactment of RGB Videos

966 indexed citations
published 2016
Authors
Justus ThiesMichael ZollhöferMarc StammingerChristian TheobaltMatthias Nießner

In The Last Decade

doi.org/10.1109/cvpr.2016.262 →

Countries where authors are citing Face2Face: Real-Time Face Capture and Reenactment of RGB Videos

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Citations

This map shows the geographic impact of Face2Face: Real-Time Face Capture and Reenactment of RGB Videos. 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 Face2Face: Real-Time Face Capture and Reenactment of RGB Videos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Face2Face: Real-Time Face Capture and Reenactment of RGB Videos more than expected).

Fields of papers citing Face2Face: Real-Time Face Capture and Reenactment of RGB Videos

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Face2Face: Real-Time Face Capture and Reenactment of RGB Videos. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Face2Face: Real-Time Face Capture and Reenactment of RGB Videos.

About Face2Face: Real-Time Face Capture and Reenactment of RGB Videos

This paper, published in 2016, received 966 indexed citations . Written by Justus Thies, Michael Zollhöfer, Marc Stamminger, Christian Theobalt and Matthias Nießner covering the research area of Neurology and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (909 citations), Artificial Intelligence (172 citations) and Signal Processing (113 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.

This paper is also available at doi.org/10.1109/cvpr.2016.262.

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