Dejia Xu

1.3k total citations · 1 hit paper
20 papers, 456 citations indexed

About

Dejia Xu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Dejia Xu has authored 20 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 4 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Dejia Xu's work include Advanced Image Processing Techniques (7 papers), Advanced Vision and Imaging (5 papers) and Computer Graphics and Visualization Techniques (4 papers). Dejia Xu is often cited by papers focused on Advanced Image Processing Techniques (7 papers), Advanced Vision and Imaging (5 papers) and Computer Graphics and Visualization Techniques (4 papers). Dejia Xu collaborates with scholars based in United States, China and Hong Kong. Dejia Xu's co-authors include Wenhan Yang, Jiaying Liu, Haofeng Huang, Zhangyang Wang, Zhiwen Fan, Yi Wang, Peihao Wang, Xiao Wang, Shuquan Rao and Lili Jiang and has published in prestigious journals such as International Journal of Computer Vision, Materials Horizons and IEEE Transactions on Multimedia.

In The Last Decade

Dejia Xu

18 papers receiving 440 citations

Hit Papers

Feature 3DGS: Supercharging 3D Gaussian Splatting to Enab... 2024 2026 2025 2024 10 20 30 40

Peers

Dejia Xu
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 326
  • Media Technology 88
  • Computer Graphics and Computer-Aided Design 53
  • Biomedical Engineering 50
  • Computational Mechanics 40
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Zhiwei Zhong China
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Mukta Prasad Switzerland
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Nannan Li China View profile →
Citations per field, relative to Dejia Xu
Dejia Xu · 1×
Citations per year, relative to Dejia Xu
Dejia Xu · 1×

Countries citing papers authored by Dejia Xu

Since Specialization
Citations

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

Fields of papers citing papers by Dejia Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dejia Xu

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3
Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields breakdown →
49
4 7
5 3
6 0
7 6
8 10
9 56
10 19
11 3
12 46
13 1
14 4
15 3
16 3
17 17
18 190
19 7
20 31

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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