Julieta Martínez

2.0k citations
7 papers · 905 indexed · 1 hit paper · h-index 4
Topics
Human Pose and Action Recognition (4 papers)Advanced Image and Video Retrieval Techniques (3 papers)Robotics and Sensor-Based Localization (2 papers)
Partner nations
CanadaUnited States

In The Last Decade

Julieta Martínez

7 papers receiving 873 citations

Hit Papers

A Simple Yet Effective Baseline for 3d Human Pose Estimation20172026202020232017250500750

Peers

Julieta Martínez
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 829
  • Human-Computer Interaction 250
  • Biomedical Engineering 210
  • Artificial Intelligence 143
  • Endocrinology, Diabetes and Metabolism 137
Replace Srinath Sridhar with:
Srinath Sridhar Germany
Umar Iqbal United States
Panna Felsen United States
Yuliang Xiu Germany
Grégory Rogez Spain
Lin Gui China
Yucheng Chen China
Haodong Duan China
Haoyi Zhu China
Emre Aksan Switzerland
Julieta Martínez relative to Srinath Sridhar Germany Srinath Sridhar's profile →
Citations per field
00.5×1.5×2.2×
Srinath Sridhar · 1×
Citations per year

Countries citing papers authored by Julieta Martínez

Since Specialization
Citations

This map shows the geographic impact of Julieta Martínez'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 Julieta Martínez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julieta Martínez more than expected).

Fields of papers citing papers by Julieta Martínez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Julieta Martínez. 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 Julieta Martínez. The network helps show where Julieta Martínez may publish in the future.

Co-authorship network of co-authors of Julieta Martínez

This figure shows the co-authorship network connecting the top 25 collaborators of Julieta Martínez. A scholar is included among the top collaborators of Julieta Martínez 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 Julieta Martínez. Julieta Martínez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

About Julieta Martínez

Julieta Martínez is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 7 papers that have together received 905 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Human-Computer Interaction (250 citations), Computer Vision and Pattern Recognition (829 citations) and Endocrinology, Diabetes and Metabolism (137 citations). Julieta Martínez has collaborated with scholars based in Canada and United States. Frequent co-authors include James J. Little, Javier Romero, Ankur Gupta, Robert J. Woodham, Shenlong Wang, Raquel Urtasun, Ioan Andrei Bârsan, John Cijiang He, Frederick Tung and Holger H. Hoos.

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.

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