Timo Bolkart
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- Computer Graphics and Visualization Techniques 4
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- Face recognition and analysis 16
- Advanced Vision and Imaging 9
- Human Pose and Action Recognition 7
- Generative Adversarial Networks and Image Synthesis 6
- Face and Expression Recognition 4
- Computational Mechanics top 1%
- 3D Shape Modeling and Analysis 18
- Human-Computer Interaction top 5%
- Signal Processing top 5%
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- Morphological variations and asymmetry 3
Timo Bolkart
30 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Computer Graphics and Computer-Aided Design 241
- Computer Vision and Pattern Recognition 1.4k
- Computational Mechanics 701
- Human-Computer Interaction 108
- Signal Processing 134
Countries citing papers authored by Timo Bolkart
This map shows the geographic impact of Timo Bolkart'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 Timo Bolkart with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timo Bolkart more than expected).
Fields of papers citing papers by Timo Bolkart
This network shows the impact of papers produced by Timo Bolkart. 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 Timo Bolkart. The network helps show where Timo Bolkart may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Timo Bolkart, 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 | 2025 | 2 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 11 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 70 | |
| 7 | 2023 | 11 | |
| 8 | 2022 | 3 | |
| 9 | Learning an animatable detailed 3D face model from in-the-wild imagesbreakdown → | 2021 | 330 |
| 10 | 2021 | 11 | |
| 11 | 2021 | 11 | |
| 12 | 2021 | 46 | |
| 13 | 2021 | 10 | |
| 14 | Convolutional Mesh Autoencoders for 3D Face Representation | 2018 | 1 |
| 15 | Learning a model of facial shape and expression from 4D scansbreakdown → | 2017 | 596 |
| 16 | 2015 | 6 | |
| 17 | 2014 | 45 | |
| 18 | 2013 | 20 | |
| 19 | Review and Comparative Analysis of Statistical Shape Spaces of 3D Data | 2012 | 1 |
| 20 | Comparative Analysis of Statistical Shape Spaces | 2012 | 2 |
About Timo Bolkart
Timo Bolkart is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics, having authored 30 papers that have together received 1.6k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (18 papers), Face recognition and analysis (16 papers), Advanced Vision and Imaging (9 papers), Human Pose and Action Recognition (7 papers), Generative Adversarial Networks and Image Synthesis (6 papers), Face and Expression Recognition (4 papers), Computer Graphics and Visualization Techniques (4 papers) and Morphological variations and asymmetry (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (241 citations), Computer Vision and Pattern Recognition (1.4k citations) and Computational Mechanics (701 citations). Timo Bolkart has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Michael J. Black, Haiwen Feng, Tianye Li, Hao Li, Javier Romero, Yao Feng, Soubhik Sanyal, Stefanie Wuhrer, Justus Thies and Wojciech Zielonka. Their work appears in journals such as NeuroImage, ACM Transactions on Graphics and Human Brain Mapping.
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.