Matías Mendieta
- Human-Computer Interaction top 2%
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- Video Surveillance and Tracking Methods 3
- Human Pose and Action Recognition 3
- Advanced Neural Network Applications 3
- Image and Video Quality Assessment 2
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data 5
- Stochastic Gradient Optimization Techniques 3
- Media Technology top 10%
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- IoT and Edge/Fog Computing 2
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- CCD and CMOS Imaging Sensors 2
- Journals
- IEEE Access (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
- Partner nations
- United StatesRussiaChina
In The Last Decade
Matías Mendieta
12 papers receiving 707 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Human-Computer Interaction 134
- Computer Vision and Pattern Recognition 460
- Artificial Intelligence 232
- Media Technology 37
- Experimental and Cognitive Psychology 45
Countries citing papers authored by Matías Mendieta
This map shows the geographic impact of Matías Mendieta'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 Matías Mendieta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matías Mendieta more than expected).
Fields of papers citing papers by Matías Mendieta
This network shows the impact of papers produced by Matías Mendieta. 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 Matías Mendieta. The network helps show where Matías Mendieta may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Matías Mendieta, 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 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 55 | |
| 4 | 2023 | 61 | |
| 5 | 2023 | 13 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 6 | |
| 8 | 2022 | 105 | |
| 9 | 2022 | 20 | |
| 10 | 3D Human Pose Estimation with Spatial and Temporal Transformersbreakdown → | 2021 | 378 |
| 11 | 2021 | 58 | |
| 12 | 2019 | 16 | |
| 13 | 2019 | 4 |
About Matías Mendieta
Matías Mendieta is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Transportation, having authored 13 papers that have together received 727 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (5 papers), Video Surveillance and Tracking Methods (3 papers), Stochastic Gradient Optimization Techniques (3 papers), Human Pose and Action Recognition (3 papers), Advanced Neural Network Applications (3 papers), IoT and Edge/Fog Computing (2 papers), CCD and CMOS Imaging Sensors (2 papers) and Image and Video Quality Assessment (2 papers). The work is most often cited by research in Human-Computer Interaction (134 citations), Computer Vision and Pattern Recognition (460 citations) and Artificial Intelligence (232 citations). Matías Mendieta has collaborated with scholars based in United States, Russia and China. Frequent co-authors include Chen Chen, Ce Zheng, Taojiannan Yang, Zhengming Ding, Sijie Zhu, Pu Wang, Minwoo Lee, Hamed Tabkhi, Arun Ravindran and Yi Zhu. Their work appears in journals such as IEEE Access, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Proceedings of the 30th ACM International Conference on Multimedia and PubMed.
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.