Sadeep Jayasumana
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- Face and Expression Recognition 4
- Image Retrieval and Classification Techniques 4
- Generative Adversarial Networks and Image Synthesis 2
- Video Surveillance and Tracking Methods 2
- Advanced Image and Video Retrieval Techniques 2
- Image Processing and 3D Reconstruction 1
- Media Technology top 5%
- Geometry and Topology top 10%
- Morphological variations and asymmetry 2
- Artificial Intelligence top 10%
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- Service-Oriented Architecture and Web Services 1
- Co-authors
- Mehrtash HarandiMathieu SalzmannHongdong LiRichard HartleyMåns LarssonAyan ChakrabartiAndreas VeitSrikumar Ramalingam
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)IEEE Signal Processing Magazine (1 paper)ANU Open Research (Australian National University) (5 papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Sadeep Jayasumana
9 papers receiving 512 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 317
- Media Technology 63
- Computational Mathematics 4
- Geometry and Topology 41
- Artificial Intelligence 145
Countries citing papers authored by Sadeep Jayasumana
This map shows the geographic impact of Sadeep Jayasumana'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 Sadeep Jayasumana with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sadeep Jayasumana more than expected).
Fields of papers citing papers by Sadeep Jayasumana
This network shows the impact of papers produced by Sadeep Jayasumana. 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 Sadeep Jayasumana. The network helps show where Sadeep Jayasumana may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Sadeep Jayasumana, 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 | Rethinking FID: Towards a Better Evaluation Metric for Image Generationbreakdown → | 2024 | 45 |
| 2 | 2024 | 1 | |
| 3 | 2020 | 1 | |
| 4 | 2018 | 81 | |
| 5 | 2015 | 157 | |
| 6 | 2014 | 21 | |
| 7 | 2013 | 18 | |
| 8 | 2013 | 176 | |
| 9 | 2013 | 20 | |
| 10 | 2013 | 0 |
About Sadeep Jayasumana
Sadeep Jayasumana is a scholar working on Computer Vision and Pattern Recognition, Geometry and Topology and Media Technology, having authored 10 papers that have together received 520 indexed citations. Recurring topics across this work include Face and Expression Recognition (4 papers), Image Retrieval and Classification Techniques (4 papers), Morphological variations and asymmetry (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Video Surveillance and Tracking Methods (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Service-Oriented Architecture and Web Services (1 paper) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (317 citations), Media Technology (63 citations) and Computational Mathematics (4 citations). Sadeep Jayasumana has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Mehrtash Harandi, Mathieu Salzmann, Hongdong Li, Richard Hartley, Måns Larsson, Ayan Chakrabarti, Andreas Veit, Srikumar Ramalingam, Philip H. S. Torr and Carsten Rother. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Signal Processing Magazine and ANU Open Research (Australian National University).
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.