Vivek Sharma
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Media Technology top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Rainer StiefelhagenLuc Van GoolAli DibaAli Mohammad PazandehHamed PirsiavashM. Saquib SarfrazReza SafdariSandeep Kumar
- Topics
- Face and Expression Recognition (4 papers)Generative Adversarial Networks and Image Synthesis (3 papers)Video Surveillance and Tracking Methods (3 papers)
- Journals
- IEEE Transactions on Biometrics Behavior and Identity Science2021 IEEE/CVF International Conference on Computer Vision (ICCV)arXiv (Cornell University)
- Partner nations
- GermanyBelgiumUnited States
In The Last Decade
Vivek Sharma
14 papers receiving 423 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 332
- Artificial Intelligence 220
- Media Technology 43
- Biomedical Engineering 19
- Radiology, Nuclear Medicine and Imaging 19
Countries citing papers authored by Vivek Sharma
This map shows the geographic impact of Vivek Sharma'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 Vivek Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivek Sharma more than expected).
Fields of papers citing papers by Vivek Sharma
This network shows the impact of papers produced by Vivek Sharma. 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 Vivek Sharma. The network helps show where Vivek Sharma may publish in the future.
Co-authorship network of co-authors of Vivek Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Vivek Sharma. A scholar is included among the top collaborators of Vivek Sharma 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 Vivek Sharma. Vivek Sharma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Vi2CLR: Video and Image for Visual Contrastive Learning of Representation | 4 |
| 2 | 31 | |
| 3 | 10 | |
| 4 | 5 | |
| 5 | 140 | |
| 6 | 6 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | Temporal 3D ConvNets Using Temporal Transition Layer | 18 |
| 10 | 1 | |
| 11 | 193 | |
| 12 | Object Discovery By Generative Adversarial & Ranking Networks. | 3 |
| 13 | A Simple and Effective Technique for Face Clustering in TV Series | 9 |
| 14 | 8 |
About Vivek Sharma
Vivek Sharma is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 14 papers that have together received 436 indexed citations. Recurring topics across this work include Face and Expression Recognition (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Video Surveillance and Tracking Methods (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (332 citations), Artificial Intelligence (220 citations) and Media Technology (43 citations). Vivek Sharma has collaborated with scholars based in Germany, Belgium and United States. Frequent co-authors include Rainer Stiefelhagen, Luc Van Gool, Ali Diba, Ali Mohammad Pazandeh, Hamed Pirsiavash, M. Saquib Sarfraz, Reza Safdari, Sandeep Kumar, Mohsen Fayyaz and Mohammad Mahdi Arzani. Their work appears in journals such as IEEE Transactions on Biometrics Behavior and Identity Science, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and arXiv (Cornell 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.