Miroslava Slavcheva
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 10%
- Aerospace Engineering top 10%
- Computer Graphics and Computer-Aided Design top 5%
- Geology top 10%
- Topics
- Advanced Vision and Imaging (7 papers)3D Shape Modeling and Analysis (5 papers)Robotics and Sensor-Based Localization (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionmediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich)
- Partner nations
- GermanyUnited States
In The Last Decade
Miroslava Slavcheva
8 papers receiving 226 citations
Peers
Comparison fields: 5 of 22
- Computer Vision and Pattern Recognition 197
- Computational Mechanics 117
- Aerospace Engineering 91
- Computer Graphics and Computer-Aided Design 81
- Geology 44
Countries citing papers authored by Miroslava Slavcheva
This map shows the geographic impact of Miroslava Slavcheva'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 Miroslava Slavcheva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miroslava Slavcheva more than expected).
Fields of papers citing papers by Miroslava Slavcheva
This network shows the impact of papers produced by Miroslava Slavcheva. 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 Miroslava Slavcheva. The network helps show where Miroslava Slavcheva may publish in the future.
Co-authorship network of co-authors of Miroslava Slavcheva
This figure shows the co-authorship network connecting the top 25 collaborators of Miroslava Slavcheva. A scholar is included among the top collaborators of Miroslava Slavcheva 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 Miroslava Slavcheva. Miroslava Slavcheva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 71 | |
| 3 | 7 | |
| 4 | Signed Distance Fields for Rigid and Deformable 3D Reconstruction | 2 |
| 5 | 110 | |
| 6 | 15 | |
| 7 | 7 | |
| 8 | 2 |
About Miroslava Slavcheva
Miroslava Slavcheva is a scholar working on Computer Graphics and Computer-Aided Design, Geology and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 232 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (7 papers), 3D Shape Modeling and Analysis (5 papers) and Robotics and Sensor-Based Localization (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (81 citations), Computer Vision and Pattern Recognition (197 citations) and Geology (44 citations). Miroslava Slavcheva has collaborated with scholars based in Germany and United States. Frequent co-authors include Slobodan Ilić, Maximilian Baust, Daniel Cremers, Nassir Navab and Wadim Kehl. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich).
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.