Removing Rain from Single Images via a Deep Detail Network

796 indexed citations

Abstract

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About

This paper, published in 2017, received 796 indexed citations. Written by Xueyang Fu, Jia‐Bin Huang, Delu Zeng, Yue Huang, Xinghao Ding and John Paisley covering the research area of Media Technology and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (760 citations), Media Technology (286 citations) and Computer Graphics and Computer-Aided Design (46 citations). Published in .

Countries where authors are citing Removing Rain from Single Images via a Deep Detail Network

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This map shows the geographic impact of Removing Rain from Single Images via a Deep Detail Network. 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 Removing Rain from Single Images via a Deep Detail Network with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Removing Rain from Single Images via a Deep Detail Network more than expected).

Fields of papers citing Removing Rain from Single Images via a Deep Detail Network

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Removing Rain from Single Images via a Deep Detail Network. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Removing Rain from Single Images via a Deep Detail Network.

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.2017.186.

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