Matías Mendieta
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Human-Computer Interaction top 2%
- Control and Systems Engineering
- Topics
- Privacy-Preserving Technologies in Data (5 papers)Video Surveillance and Tracking Methods (3 papers)Stochastic Gradient Optimization Techniques (3 papers)
- Journals
- IEEE Access2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United StatesRussiaChina
In The Last Decade
Matías Mendieta
12 papers receiving 707 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 460
- Artificial Intelligence 232
- Biomedical Engineering 152
- Human-Computer Interaction 134
- Control and Systems Engineering 57
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 of co-authors of Matías Mendieta
This figure shows the co-authorship network connecting the top 25 collaborators of Matías Mendieta. A scholar is included among the top collaborators of Matías Mendieta 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 Matías Mendieta. Matías Mendieta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 55 | |
| 4 | 61 | |
| 5 | 13 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 105 | |
| 9 | 20 | |
| 10 | 3D Human Pose Estimation with Spatial and Temporal Transformersbreakdown → | 378 |
| 11 | 58 | |
| 12 | 16 | |
| 13 | 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) and Stochastic Gradient Optimization Techniques (3 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) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.