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
- Generative Adversarial Networks and Image Synthesis
- Video Surveillance and Tracking Methods
Papers in
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- Generative Adversarial Networks and Image Synthesis 4
- Human Pose and Action Recognition 4
- Advanced Vision and Imaging 3
- Video Analysis and Summarization 2
- Multimodal Machine Learning Applications 1
- Image Enhancement Techniques 1
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- Machine Learning and Data Classification 2
- Co-authors
- Stephen Lombardi (1 shared paper)Yaser Sheikh (1 shared paper)Jason Saragih (1 shared paper)Gabriel Schwartz (1 shared paper)Tomas Simon (1 shared paper)Sebastian Nowozin (2 shared papers)Peter Gehler (2 shared papers)Leonid Sigal (4 shared papers)
- Journals
- ACM Transactions on Graphics (1 paper)Data Mining and Knowledge Discovery (1 paper)Lecture notes in computer science (2 papers)International Conference on Learning Representations (1 paper)Uncertainty in Artificial Intelligence (1 paper)
- Partner nations
- GermanyUnited StatesCanada
In The Last Decade
Andreas Lehrmann
10 papers receiving 672 citations
Andreas Lehrmann's Hit Papers
Peers
Comparison fields: 5 of 58
- Computer Graphics and Computer-Aided Design 316
- Computer Vision and Pattern Recognition 609
- Computational Mechanics 268
- Human-Computer Interaction 29
- Geology 27
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 20 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 | 492 |
| 2 | 2014 | 122 | |
| 3 | 2018 | 33 | |
| 4 | 2013 | 32 | |
| 5 | 2012 | 5 | |
| 6 | 2020 | 4 | |
| 7 | PROVIDE: A Probabilistic Framework for Unsupervised Video Decomposition | 2021 | 2 |
| 8 | Non-parametric Structured Output Networks | 2017 | 2 |
| 9 | Variational Autoencoders with Jointly Optimized Latent Dependency Structure | 2018 | 2 |
| 10 | Structural Decompositions for End-to-End Relighting. | 2019 | 1 |
| 11 | 2023 | 0 |
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 11 papers that have together received 695 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (4 papers), Human Pose and Action Recognition (4 papers), Advanced Vision and Imaging (3 papers), Machine Learning and Data Classification (2 papers), Video Analysis and Summarization (2 papers), Computer Graphics and Visualization Techniques (2 papers), Multimodal Machine Learning Applications (1 paper) and Image Enhancement Techniques (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (316 citations), Computer Vision and Pattern Recognition (609 citations), Computational Mechanics (268 citations), Human-Computer Interaction (29 citations) and Geology (27 citations). Andreas Lehrmann has collaborated with scholars based in Germany, United States and Canada. Frequent co-authors include Stephen Lombardi, Yaser Sheikh, Jason Saragih, Gabriel Schwartz, Tomas Simon, Sebastian Nowozin, Peter Gehler, Leonid Sigal, Greg Mori and Jiawei He. Their work appears in journals such as ACM Transactions on Graphics, Data Mining and Knowledge Discovery, Lecture notes in computer science, International Conference on Learning Representations and Uncertainty in Artificial Intelligence.
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.