Makarand Tapaswi
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- Video Analysis and Summarization 12
- Multimodal Machine Learning Applications 12
- Human Pose and Action Recognition 11
- Video Surveillance and Tracking Methods 11
- Face recognition and analysis 10
- Face and Expression Recognition 5
- Artificial Intelligence top 2%
- Signal Processing top 5%
- Speech and Audio Processing 6
- Music and Audio Processing 6
- Human-Computer Interaction top 10%
- Co-authors
- Rainer StiefelhagenIvan LaptevMartin BäumlJosef ŠivicJean-Baptiste AlayracAntoine MiechDimitri ZhukovShizhe Chen
In The Last Decade
Makarand Tapaswi
37 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 1.1k
- Artificial Intelligence 526
- Signal Processing 133
- Human-Computer Interaction 28
- Language and Linguistics 19
Countries citing papers authored by Makarand Tapaswi
This map shows the geographic impact of Makarand Tapaswi'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 Makarand Tapaswi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Makarand Tapaswi more than expected).
Fields of papers citing papers by Makarand Tapaswi
This network shows the impact of papers produced by Makarand Tapaswi. 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 Makarand Tapaswi. The network helps show where Makarand Tapaswi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Makarand Tapaswi, 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 | 2025 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 5 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 7 | |
| 8 | 2021 | 82 | |
| 9 | HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million\n Narrated Video Clipsbreakdown → | 2019 | 521 |
| 10 | 2018 | 13 | |
| 11 | 2016 | 51 | |
| 12 | 2015 | 49 | |
| 13 | KIT at MediaEval 2015 - Evaluating Visual Cues for Affective Impact of Movies Task | 2015 | 20 |
| 14 | 2015 | 11 | |
| 15 | 2014 | 4 | |
| 16 | 2014 | 19 | |
| 17 | 2014 | 41 | |
| 18 | QCompere @ REPERE 2013 | 2013 | 3 |
| 19 | KIT at MediaEval 2012 - Content - based Genre Classification with Visual Cues. | 2012 | 2 |
| 20 | 2010 | 1 |
About Makarand Tapaswi
Makarand Tapaswi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 39 papers that have together received 1.2k indexed citations. Recurring topics across this work include Video Analysis and Summarization (12 papers), Multimodal Machine Learning Applications (12 papers), Human Pose and Action Recognition (11 papers), Video Surveillance and Tracking Methods (11 papers), Face recognition and analysis (10 papers), Speech and Audio Processing (6 papers), Music and Audio Processing (6 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Artificial Intelligence (526 citations) and Signal Processing (133 citations). Makarand Tapaswi has collaborated with scholars based in Germany, India and France. Frequent co-authors include Rainer Stiefelhagen, Ivan Laptev, Martin Bäuml, Josef Šivic, Jean-Baptiste Alayrac, Antoine Miech, Dimitri Zhukov, Shizhe Chen, Cordelia Schmid and Ziad Al-Halah. Their work appears in journals such as Computer Vision and Image Understanding, IEEE Transactions on Biometrics Behavior and Identity Science and International Journal of Multimedia Information Retrieval.
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.