Davis Rempe
Impact in
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
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- Human Pose and Action Recognition
- Advanced Vision and Imaging
Papers in
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- Human Pose and Action Recognition 5
- Advanced Vision and Imaging 2
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- 3D Shape Modeling and Analysis 6
- Advanced Numerical Analysis Techniques 2
- Co-authors
- Or Litany (3 shared papers)Sanja Fidler (2 shared papers)Leonidas Guibas (8 shared papers)Jonah Philion (1 shared paper)Baishakhi Ray (1 shared paper)Ziyuan Zhong (1 shared paper)Danfei Xu (1 shared paper)Xue Bin Peng (2 shared papers)
- Journals
- Repository for Publications and Research Data (ETH Zurich) (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)Computer Vision and Pattern Recognition (1 paper)Neural Information Processing Systems (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Davis Rempe
11 papers receiving 212 citations
Peers
Comparison fields: 5 of 38
- Automotive Engineering 92
- Computer Vision and Pattern Recognition 77
- Control and Systems Engineering 77
- Software 12
- Computer Graphics and Computer-Aided Design 10
Countries citing papers authored by Davis Rempe
This map shows the geographic impact of Davis Rempe'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 Davis Rempe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Davis Rempe more than expected).
Fields of papers citing papers by Davis Rempe
This network shows the impact of papers produced by Davis Rempe. 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 Davis Rempe. The network helps show where Davis Rempe may publish in the future.
Co-authors
The 25 scholars most cited alongside Davis Rempe, 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 | 2022 | 78 | |
| 2 | 2023 | 58 | |
| 3 | 2023 | 43 | |
| 4 | 2024 | 13 | |
| 5 | 2024 | 8 | |
| 6 | Multiview Aggregation for Learning Category-Specific Shape Reconstruction | 2019 | 5 |
| 7 | 2020 | 4 | |
| 8 | 2021 | 4 | |
| 9 | 2023 | 3 | |
| 10 | Learning Generalizable Final-State Dynamics of 3D Rigid Objects | 2019 | 2 |
| 11 | 2024 | 1 | |
| 12 | 2025 | 0 |
About Davis Rempe
Davis Rempe is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Control and Systems Engineering, Automotive Engineering and Computer Graphics and Computer-Aided Design, having authored 12 papers that have together received 219 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (6 papers), Human Pose and Action Recognition (5 papers), Autonomous Vehicle Technology and Safety (3 papers), Human Motion and Animation (3 papers), Advanced Vision and Imaging (2 papers), Traffic control and management (2 papers), Computer Graphics and Visualization Techniques (2 papers) and Advanced Numerical Analysis Techniques (2 papers). The work is most often cited by research in Automotive Engineering (92 citations), Computer Vision and Pattern Recognition (77 citations), Control and Systems Engineering (77 citations), Software (12 citations) and Computer Graphics and Computer-Aided Design (10 citations). Davis Rempe has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Or Litany, Sanja Fidler, Leonidas Guibas, Jonah Philion, Baishakhi Ray, Ziyuan Zhong, Danfei Xu, Xue Bin Peng, Yuxiao Chen and Sushant Veer. Their work appears in journals such as Repository for Publications and Research Data (ETH Zurich), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Computer Vision and Pattern Recognition, Neural Information Processing Systems and HAL (Le Centre pour la Communication Scientifique Directe).
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.