Learning Rich Features for Image Manipulation Detection
Impact in
- Media Technology 154
Classified as
- Authors
- Peng ZhouXintong HanVlad I. MorariuLarry Steven Davis
In The Last Decade
doi.org/10.1109/cvpr.2018.00116 →Countries where authors are citing Learning Rich Features for Image Manipulation Detection
This map shows the geographic impact of Learning Rich Features for Image Manipulation Detection. 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 Learning Rich Features for Image Manipulation Detection with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Learning Rich Features for Image Manipulation Detection more than expected).
Fields of papers citing Learning Rich Features for Image Manipulation Detection
This network shows the impact of Learning Rich Features for Image Manipulation Detection. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Learning Rich Features for Image Manipulation Detection.
About Learning Rich Features for Image Manipulation Detection
This paper, published in 2018, received 518 indexed citations . Written by Peng Zhou, Xintong Han, Vlad I. Morariu and Larry Steven Davis covering the research area of Computer Vision and Pattern Recognition and Media Technology. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (482 citations), Media Technology (154 citations), Artificial Intelligence (114 citations), Biophysics (65 citations) and Law (39 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.2018.00116.