Vijay Badrinarayanan
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Aerospace Engineering top 10%
- Geology top 5%
- Automotive Engineering top 10%
- Co-authors
- Roberto CipollaAndrew RabinovichChen‐Yu LeeAnkur HandaAlex KendallIgnas BudvytisChen ZhaoFabio Galasso
- Topics
- Advanced Image and Video Retrieval Techniques (9 papers)Video Surveillance and Tracking Methods (5 papers)Video Analysis and Summarization (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionIEEE/ACM Transactions on Networking
- Partner nations
- United KingdomFranceNorway
In The Last Decade
Vijay Badrinarayanan
17 papers receiving 843 citations
Peers
Comparison fields: 5 of 86
- Computer Vision and Pattern Recognition 666
- Artificial Intelligence 189
- Aerospace Engineering 146
- Geology 90
- Automotive Engineering 68
Countries citing papers authored by Vijay Badrinarayanan
This map shows the geographic impact of Vijay Badrinarayanan'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 Vijay Badrinarayanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vijay Badrinarayanan more than expected).
Fields of papers citing papers by Vijay Badrinarayanan
This network shows the impact of papers produced by Vijay Badrinarayanan. 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 Vijay Badrinarayanan. The network helps show where Vijay Badrinarayanan may publish in the future.
Co-authorship network of co-authors of Vijay Badrinarayanan
This figure shows the co-authorship network connecting the top 25 collaborators of Vijay Badrinarayanan. A scholar is included among the top collaborators of Vijay Badrinarayanan 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 Vijay Badrinarayanan. Vijay Badrinarayanan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 147 | |
| 2 | 22 | |
| 3 | GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks | 122 |
| 4 | 101 | |
| 5 | 60 | |
| 6 | 135 | |
| 7 | 46 | |
| 8 | 13 | |
| 9 | 42 | |
| 10 | 10 | |
| 11 | 7 | |
| 12 | 30 | |
| 13 | 88 | |
| 14 | 18 | |
| 15 | Geometric Layout Based Graphical Model for Multi-Part Object Tracking | 2 |
| 16 | 41 | |
| 17 | 4 |
About Vijay Badrinarayanan
Vijay Badrinarayanan is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Biophysics, having authored 17 papers that have together received 888 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (9 papers), Video Surveillance and Tracking Methods (5 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (666 citations), Geology (90 citations) and Human-Computer Interaction (36 citations). Vijay Badrinarayanan has collaborated with scholars based in United Kingdom, France and Norway. Frequent co-authors include Roberto Cipolla, Andrew Rabinovich, Chen‐Yu Lee, Ankur Handa, Alex Kendall, Ignas Budvytis, Chen Zhao, Fabio Galasso, Viorica Pătrăucean and Simon Stent. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE/ACM Transactions on Networking.
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.