Shiran Zada
- Computer Vision and Pattern Recognition top 2%
- Computer Graphics and Computer-Aided Design top 2%
- Artificial Intelligence top 10%
- Computational Mechanics top 10%
- Control and Systems Engineering
- Co-authors
- Inbar MosseriOmer TovTali DekelMichal IraniOran LangHui‐Wen ChangBahjat KawarVarun Jampani
- Topics
- Generative Adversarial Networks and Image Synthesis (5 papers)Computer Graphics and Visualization Techniques (4 papers)Advanced Vision and Imaging (3 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- ACM Transactions on Graphics
- Partner nations
- United StatesIsraelSingapore
In The Last Decade
Shiran Zada
7 papers receiving 510 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Computer Vision and Pattern Recognition 394
- Computer Graphics and Computer-Aided Design 143
- Artificial Intelligence 92
- Computational Mechanics 71
- Control and Systems Engineering 42
Countries citing papers authored by Shiran Zada
This map shows the geographic impact of Shiran Zada'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 Shiran Zada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shiran Zada more than expected).
Fields of papers citing papers by Shiran Zada
This network shows the impact of papers produced by Shiran Zada. 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 Shiran Zada. The network helps show where Shiran Zada may publish in the future.
Co-authorship network of co-authors of Shiran Zada
This figure shows the co-authorship network connecting the top 25 collaborators of Shiran Zada. A scholar is included among the top collaborators of Shiran Zada 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 Shiran Zada. Shiran Zada 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 | 0 | |
| 6 | 87 | |
| 7 | 22 | |
| 8 | Imagic: Text-Based Real Image Editing with Diffusion Modelsbreakdown → | 364 |
About Shiran Zada
Shiran Zada is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Signal Processing, having authored 8 papers that have together received 524 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (5 papers), Computer Graphics and Visualization Techniques (4 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (143 citations), Computer Vision and Pattern Recognition (394 citations) and Computational Mechanics (71 citations). Shiran Zada has collaborated with scholars based in United States, Israel and Singapore. Frequent co-authors include Inbar Mosseri, Omer Tov, Tali Dekel, Michal Irani, Oran Lang, Hui‐Wen Chang, Bahjat Kawar, Varun Jampani, Michael Niemeyer and Ben Mildenhall. Their work appears in journals such as ACM Transactions on Graphics.
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.