Andreas Lehrmann
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Advanced Vision and Imaging 3
- Generative Adversarial Networks and Image Synthesis 2
- Human Pose and Action Recognition 2
- Image Enhancement Techniques 1
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- Machine Learning and Data Classification 2
- Co-authors
- Yaser Sheikh (1 shared paper)Tomas Simon (1 shared paper)Jason Saragih (1 shared paper)Stephen Lombardi (1 shared paper)Gabriel Schwartz (1 shared paper)Sebastian Nowozin (2 shared papers)Peter Gehler (2 shared papers)Leonid Sigal (2 shared papers)
- Journals
- Data Mining and Knowledge Discovery (1 paper)ACM Transactions on Graphics (1 paper)Uncertainty in Artificial Intelligence (1 paper)Max Planck Digital Library (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Andreas Lehrmann
8 papers receiving 560 citations
Andreas Lehrmann's Hit Papers
Peers
Comparison fields: 5 of 53
- Computer Graphics and Computer-Aided Design 280
- Computer Vision and Pattern Recognition 501
- Computational Mechanics 232
- Human-Computer Interaction 24
- Geology 24
Countries citing papers authored by Andreas Lehrmann
This map shows the geographic impact of Andreas Lehrmann'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 Andreas Lehrmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Lehrmann more than expected).
Fields of papers citing papers by Andreas Lehrmann
This network shows the impact of papers produced by Andreas Lehrmann. 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 Andreas Lehrmann. The network helps show where Andreas Lehrmann may publish in the future.
Co-authors
The 14 scholars most cited alongside Andreas Lehrmann, 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 | Neural volumes Hit paper breakdown → | 2019 | 431 |
| 2 | 2014 | 109 | |
| 3 | 2013 | 27 | |
| 4 | 2012 | 4 | |
| 5 | PROVIDE: A Probabilistic Framework for Unsupervised Video Decomposition | 2021 | 2 |
| 6 | Non-parametric Structured Output Networks | 2017 | 2 |
| 7 | Variational Autoencoders with Jointly Optimized Latent Dependency Structure | 2018 | 1 |
| 8 | Structural Decompositions for End-to-End Relighting. | 2019 | 1 |
About Andreas Lehrmann
Andreas Lehrmann is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Graphics and Computer-Aided Design, Molecular Biology and Control and Systems Engineering, having authored 8 papers that have together received 577 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Human Pose and Action Recognition (2 papers), Machine Learning and Data Classification (2 papers), Computer Graphics and Visualization Techniques (2 papers), Image Enhancement Techniques (1 paper), Gene expression and cancer classification (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (280 citations), Computer Vision and Pattern Recognition (501 citations), Computational Mechanics (232 citations), Human-Computer Interaction (24 citations) and Geology (24 citations). Andreas Lehrmann has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Yaser Sheikh, Tomas Simon, Jason Saragih, Stephen Lombardi, Gabriel Schwartz, Sebastian Nowozin, Peter Gehler, Leonid Sigal, Kay Nieselt and Polina Zablotskaia. Their work appears in journals such as Data Mining and Knowledge Discovery, ACM Transactions on Graphics, Uncertainty in Artificial Intelligence, Max Planck Digital Library and arXiv (Cornell University).
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.