Jeremy Reizenstein
- Computer Vision and Pattern Recognition top 2%
- Computational Mechanics top 5%
- Computer Graphics and Computer-Aided Design top 2%
- Aerospace Engineering top 10%
- Geology top 5%
- Co-authors
- David NovotnýJustin JohnsonSteve BransonShubham TulsianiNikhila RaviChristoph LassnerРоман ШаповаловPhilipp Henzler
- Topics
- Advanced Vision and Imaging (3 papers)3D Shape Modeling and Analysis (2 papers)Advanced Image and Video Retrieval Techniques (1 paper)
- Journals
- ACM Transactions on Mathematical SoftwareJournal of Algebra2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United KingdomIsraelCanada
In The Last Decade
Jeremy Reizenstein
6 papers receiving 524 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 416
- Computational Mechanics 236
- Computer Graphics and Computer-Aided Design 174
- Aerospace Engineering 90
- Geology 77
Countries citing papers authored by Jeremy Reizenstein
This map shows the geographic impact of Jeremy Reizenstein'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 Jeremy Reizenstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeremy Reizenstein more than expected).
Fields of papers citing papers by Jeremy Reizenstein
This network shows the impact of papers produced by Jeremy Reizenstein. 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 Jeremy Reizenstein. The network helps show where Jeremy Reizenstein may publish in the future.
Co-authorship network of co-authors of Jeremy Reizenstein
This figure shows the co-authorship network connecting the top 25 collaborators of Jeremy Reizenstein. A scholar is included among the top collaborators of Jeremy Reizenstein 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 Jeremy Reizenstein. Jeremy Reizenstein is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 1 | |
| 3 | Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructionbreakdown → | 183 |
| 4 | Accelerating 3D deep learning with PyTorch3Dbreakdown → | 334 |
| 5 | 7 | |
| 6 | PerspectiveNet: A Scene-consistent Image Generator for New View Synthesis in Real Indoor Environments | 14 |
About Jeremy Reizenstein
Jeremy Reizenstein is a scholar working on Discrete Mathematics and Combinatorics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 6 papers that have together received 546 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (3 papers), 3D Shape Modeling and Analysis (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (174 citations), Computer Vision and Pattern Recognition (416 citations) and Geology (77 citations). Jeremy Reizenstein has collaborated with scholars based in United Kingdom, Israel and Canada. Frequent co-authors include David Novotný, Justin Johnson, Steve Branson, Shubham Tulsiani, Nikhila Ravi, Christoph Lassner, Роман Шаповалов, Philipp Henzler, L. Sbordone and Patrick Labatut. Their work appears in journals such as ACM Transactions on Mathematical Software, Journal of Algebra and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.