Inbar Mosseri
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Artificial Intelligence top 5%
- Computational Mechanics top 10%
- Computer Graphics and Computer-Aided Design top 2%
- Co-authors
- Tali DekelOran LangMichal IraniOmer TovAriel EphratWilliam T. FreemanShiran ZadaAvinatan Hassidim
- Topics
- Generative Adversarial Networks and Image Synthesis (8 papers)Video Analysis and Summarization (3 papers)Image and Signal Denoising Methods (2 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignSignal ProcessingComputer Vision and Pattern Recognition
- Journals
- ACM Transactions on Graphics2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- IsraelUnited StatesSingapore
In The Last Decade
Inbar Mosseri
14 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 654
- Signal Processing 356
- Artificial Intelligence 261
- Computational Mechanics 126
- Computer Graphics and Computer-Aided Design 115
Countries citing papers authored by Inbar Mosseri
This map shows the geographic impact of Inbar Mosseri'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 Inbar Mosseri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inbar Mosseri more than expected).
Fields of papers citing papers by Inbar Mosseri
This network shows the impact of papers produced by Inbar Mosseri. 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 Inbar Mosseri. The network helps show where Inbar Mosseri may publish in the future.
Co-authorship network of co-authors of Inbar Mosseri
This figure shows the co-authorship network connecting the top 25 collaborators of Inbar Mosseri. A scholar is included among the top collaborators of Inbar Mosseri 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 Inbar Mosseri. Inbar Mosseri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | Lumiere: A Space-Time Diffusion Model for Video Generationbreakdown → | 45 |
| 5 | 22 | |
| 6 | Imagic: Text-Based Real Image Editing with Diffusion Modelsbreakdown → | 364 |
| 7 | 44 | |
| 8 | 12 | |
| 9 | 0 | |
| 10 | 19 | |
| 11 | 53 | |
| 12 | Looking to listen at the cocktail partybreakdown → | 376 |
| 13 | Face Synthesis from Facial Identity Features. | 7 |
| 14 | 62 | |
| 15 | 61 |
About Inbar Mosseri
Inbar Mosseri is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Biophysics, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (8 papers), Video Analysis and Summarization (3 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (115 citations), Signal Processing (356 citations) and Computer Vision and Pattern Recognition (654 citations). Inbar Mosseri has collaborated with scholars based in Israel, United States and Singapore. Frequent co-authors include Tali Dekel, Oran Lang, Michal Irani, Omer Tov, Ariel Ephrat, William T. Freeman, Shiran Zada, Avinatan Hassidim, Michael Rubinstein and Kevin Wilson. Their work appears in journals such as ACM Transactions on Graphics, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 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.