Robin Rombach
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- Computer Graphics and Visualization Techniques 2
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- Generative Adversarial Networks and Image Synthesis 7
- Multimodal Machine Learning Applications 3
- Advanced Vision and Imaging 2
- Advanced Image Processing Techniques 2
- Advanced Image and Video Retrieval Techniques 1
- Artificial Intelligence top 0.5%
- Signal Processing top 2%
- Health Informatics top 2%
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- Advanced Neuroimaging Techniques and Applications 1
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- Model Reduction and Neural Networks 1
- Co-authors
- Andreas BlattmannBjörn OmmerPatrick EsserSeung Wook KimSanja FidlerTim DockhornKarsten KreisHuan Ling
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- GermanyCanadaUnited States
In The Last Decade
Robin Rombach
7 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 173
- Computer Graphics and Computer-Aided Design 827
- Computer Vision and Pattern Recognition 4.0k
- Artificial Intelligence 1.6k
- Signal Processing 445
- Health Informatics 54
Countries citing papers authored by Robin Rombach
This map shows the geographic impact of Robin Rombach'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 Robin Rombach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robin Rombach more than expected).
Fields of papers citing papers by Robin Rombach
This network shows the impact of papers produced by Robin Rombach. 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 Robin Rombach. The network helps show where Robin Rombach may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Robin Rombach, 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 | 13 | |
| 2 | 2023 | 25 | |
| 3 | On Distillation of Guided Diffusion Modelsbreakdown → | 2023 | 117 |
| 4 | Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelsbreakdown → | 2023 | 249 |
| 5 | High-Resolution Image Synthesis with Latent Diffusion Modelsbreakdown → | 2022 | 6044 |
| 6 | Network Fusion for Content Creation with Conditional INNs. | 2020 | 1 |
| 7 | 2020 | 5 |
About Robin Rombach
Robin Rombach is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 7 papers that have together received 6.5k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (7 papers), Multimodal Machine Learning Applications (3 papers), Computer Graphics and Visualization Techniques (2 papers), Advanced Vision and Imaging (2 papers), Advanced Image Processing Techniques (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Model Reduction and Neural Networks (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (827 citations), Computer Vision and Pattern Recognition (4.0k citations) and Artificial Intelligence (1.6k citations). Robin Rombach has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Andreas Blattmann, Björn Ommer, Patrick Esser, Seung Wook Kim, Sanja Fidler, Tim Dockhorn, Karsten Kreis, Huan Ling, Chenlin Meng and Jonathan Ho. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 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.