Omer Bar-Tal
Impact in
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- Computer Graphics and Visualization Techniques
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- Generative Adversarial Networks and Image Synthesis
- Advanced Vision and Imaging
- Video Analysis and Summarization
- Advanced Image Processing Techniques
- Image Retrieval and Classification Techniques
Papers in ⓘ
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- Computer Graphics and Visualization Techniques 1
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- Generative Adversarial Networks and Image Synthesis 4
- Face recognition and analysis 2
- Video Analysis and Summarization 1
- Handwritten Text Recognition Techniques 1
- Co-authors
- Tali Dekel (4 shared papers)Shai Bagon (3 shared papers)Narek Tumanyan (2 shared papers)Michael Rubinstein (1 shared paper)Oliver Wang (1 shared paper)Tomer Michaeli (1 shared paper)Hila Chefer (1 shared paper)Omer Tov (1 shared paper)
- Journals
- ACM Transactions on Graphics (1 paper)Nature Biotechnology (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- IsraelUnited StatesHong Kong
In The Last Decade
Omer Bar-Tal
6 papers receiving 118 citations
Hit Papers
Peers
Comparison fields: 5 of 36
- Computer Graphics and Computer-Aided Design 23
- Computer Vision and Pattern Recognition 90
- Signal Processing 15
- Health Informatics 1
- Control and Systems Engineering 15
Countries citing papers authored by Omer Bar-Tal
This map shows the geographic impact of Omer Bar-Tal'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 Omer Bar-Tal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Omer Bar-Tal more than expected).
Fields of papers citing papers by Omer Bar-Tal
This network shows the impact of papers produced by Omer Bar-Tal. 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 Omer Bar-Tal. The network helps show where Omer Bar-Tal may publish in the future.
Co-authors
The 25 scholars most cited alongside Omer Bar-Tal, 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 | 64 | |
| 2 | Lumiere: A Space-Time Diffusion Model for Video Generation Hit paper breakdown → | 2024 | 45 |
| 3 | 2024 | 6 | |
| 4 | 2025 | 2 | |
| 5 | 2025 | 1 | |
| 6 | 2023 | 1 |
About Omer Bar-Tal
Omer Bar-Tal is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Biophysics, Control and Systems Engineering and Molecular Biology, having authored 6 papers that have together received 119 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (4 papers), Face recognition and analysis (2 papers), Single-cell and spatial transcriptomics (1 paper), Computer Graphics and Visualization Techniques (1 paper), Cell Image Analysis Techniques (1 paper), Video Analysis and Summarization (1 paper), Human Motion and Animation (1 paper) and Handwritten Text Recognition Techniques (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (23 citations), Computer Vision and Pattern Recognition (90 citations), Signal Processing (15 citations), Health Informatics (1 citation) and Control and Systems Engineering (15 citations). Omer Bar-Tal has collaborated with scholars based in Israel, United States and Hong Kong. Frequent co-authors include Tali Dekel, Shai Bagon, Narek Tumanyan, Michael Rubinstein, Oliver Wang, Tomer Michaeli, Hila Chefer, Omer Tov, Ariel Ephrat and Inbar Mosseri. Their work appears in journals such as ACM Transactions on Graphics, Nature Biotechnology and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.