Face Alignment Across Large Poses: A 3D Solution

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This paper, published in 1950, received 660 indexed citations. Written by Xiangyu Zhu, Zhen Lei, Xiaoming Liu, Hailin Shi and Stan Z. Li covering the research area of Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (624 citations), Signal Processing (168 citations) and Computational Mechanics (119 citations). Published in .

Countries where authors are citing Face Alignment Across Large Poses: A 3D Solution

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This map shows the geographic impact of Face Alignment Across Large Poses: A 3D Solution. 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 Face Alignment Across Large Poses: A 3D Solution with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Face Alignment Across Large Poses: A 3D Solution more than expected).

Fields of papers citing Face Alignment Across Large Poses: A 3D Solution

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Face Alignment Across Large Poses: A 3D Solution. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Face Alignment Across Large Poses: A 3D Solution.

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.2016.23.

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