Gabriel Schwartz
- Computer Vision and Pattern Recognition top 1%
- Computer Graphics and Computer-Aided Design top 0.5%
- Computational Mechanics top 2%
- Aerospace Engineering
- Control and Systems Engineering
- Co-authors
- Tomas SimonYaser SheikhJason SaragihStephen LombardiAndreas LehrmannKo NishinoMichael ZollhoeferJunxuan Li
- Topics
- Advanced Vision and Imaging (6 papers)Computer Graphics and Visualization Techniques (5 papers)Advanced Image and Video Retrieval Techniques (2 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceACM Transactions on GraphicsInternational Journal of Computer Vision
- Partner nations
- United StatesIsrael
In The Last Decade
Gabriel Schwartz
12 papers receiving 787 citations
Hit Papers
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 671
- Computer Graphics and Computer-Aided Design 407
- Computational Mechanics 373
- Aerospace Engineering 81
- Control and Systems Engineering 55
Countries citing papers authored by Gabriel Schwartz
This map shows the geographic impact of Gabriel Schwartz'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 Gabriel Schwartz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Schwartz more than expected).
Fields of papers citing papers by Gabriel Schwartz
This network shows the impact of papers produced by Gabriel Schwartz. 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 Gabriel Schwartz. The network helps show where Gabriel Schwartz may publish in the future.
Co-authorship network of co-authors of Gabriel Schwartz
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Schwartz. A scholar is included among the top collaborators of Gabriel Schwartz 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 Gabriel Schwartz. Gabriel Schwartz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 33 | |
| 4 | 3 | |
| 5 | 18 | |
| 6 | 150 | |
| 7 | 38 | |
| 8 | Neural volumesbreakdown → | 418 |
| 9 | 46 | |
| 10 | 25 | |
| 11 | 37 | |
| 12 | 49 |
About Gabriel Schwartz
Gabriel Schwartz is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 12 papers that have together received 819 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (6 papers), Computer Graphics and Visualization Techniques (5 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (407 citations), Computer Vision and Pattern Recognition (671 citations) and Computational Mechanics (373 citations). Gabriel Schwartz has collaborated with scholars based in United States and Israel. Frequent co-authors include Tomas Simon, Yaser Sheikh, Jason Saragih, Stephen Lombardi, Andreas Lehrmann, Ko Nishino, Michael Zollhoefer, Junxuan Li, Giljoo Nam and Shunsuke Saito. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and International Journal of Computer Vision.
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.