Vladimir G. Kim
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- Computer Graphics and Visualization Techniques 31
- Geology top 0.2%
- 3D Surveying and Cultural Heritage 8
- Computational Mechanics top 0.2%
- 3D Shape Modeling and Analysis 49
- Advanced Numerical Analysis Techniques 17
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- Image Processing and 3D Reconstruction 14
- Advanced Vision and Imaging 11
- Human Pose and Action Recognition 8
- Environmental Engineering top 2%
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- Plasma Diagnostics and Applications 11
- Co-authors
- Thomas FunkhouserYaron LipmanLeonidas GuibasSiddhartha ChaudhuriQixing HuangNiloy J. MitraAleksey GolovinskiyAlla Sheffer
- Journals
- ACM Transactions on Graphics (21 papers)The Laryngoscope (1 paper)Computer Graphics Forum (9 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Vladimir G. Kim
76 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Computer Graphics and Computer-Aided Design 1.3k
- Geology 1.0k
- Computational Mechanics 2.5k
- Computer Vision and Pattern Recognition 2.0k
- Environmental Engineering 514
Countries citing papers authored by Vladimir G. Kim
This map shows the geographic impact of Vladimir G. Kim'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 Vladimir G. Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladimir G. Kim more than expected).
Fields of papers citing papers by Vladimir G. Kim
This network shows the impact of papers produced by Vladimir G. Kim. 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 Vladimir G. Kim. The network helps show where Vladimir G. Kim may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vladimir G. Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 0 | |
| 4 | 2021 | 28 | |
| 5 | 2020 | 29 | |
| 6 | Learning to Generate Textures on 3D Meshes | 2019 | 3 |
| 7 | 2019 | 41 | |
| 8 | 2018 | 4 | |
| 9 | 2018 | 4 | |
| 10 | 2018 | 10 | |
| 11 | 2018 | 1 | |
| 12 | 2017 | 64 | |
| 13 | A scalable active framework for region annotation in 3D shape collectionsbreakdown → | 2016 | 724 |
| 14 | 2014 | 45 | |
| 15 | 2012 | 10 | |
| 16 | 2011 | 210 | |
| 17 | 2003 | 7 | |
| 18 | 1998 | 9 | |
| 19 | 1996 | 19 | |
| 20 | 1995 | 1 |
About Vladimir G. Kim
Vladimir G. Kim is a scholar working on Computer Graphics and Computer-Aided Design, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 79 papers that have together received 3.9k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (49 papers), Computer Graphics and Visualization Techniques (31 papers), Advanced Numerical Analysis Techniques (17 papers), Image Processing and 3D Reconstruction (14 papers), Plasma Diagnostics and Applications (11 papers), Advanced Vision and Imaging (11 papers), 3D Surveying and Cultural Heritage (8 papers) and Human Pose and Action Recognition (8 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (1.3k citations), Geology (1.0k citations) and Computational Mechanics (2.5k citations). Vladimir G. Kim has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Thomas Funkhouser, Yaron Lipman, Leonidas Guibas, Siddhartha Chaudhuri, Qixing Huang, Niloy J. Mitra, Aleksey Golovinskiy, Alla Sheffer, Duygu Ceylan and Hao Su. Their work appears in journals such as ACM Transactions on Graphics, The Laryngoscope and Computer Graphics Forum.
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.