Brais Martínez

3.5k total citations
37 papers, 1.3k citations indexed

About

Brais Martínez is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Brais Martínez has authored 37 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 9 papers in Experimental and Cognitive Psychology. Recurrent topics in Brais Martínez's work include Face recognition and analysis (14 papers), Face and Expression Recognition (11 papers) and Emotion and Mood Recognition (9 papers). Brais Martínez is often cited by papers focused on Face recognition and analysis (14 papers), Face and Expression Recognition (11 papers) and Emotion and Mood Recognition (9 papers). Brais Martínez collaborates with scholars based in United Kingdom, Spain and Netherlands. Brais Martínez's co-authors include Maja Pantić, Michel Valstar, Xavier Binefa, Bihan Jiang, Stavros Petridis, Georgios Tzimiropoulos, Adrian Bulat, Jing Yang, Pingchuan Ma and Timur Almaev and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and International Journal of Computer Vision.

In The Last Decade

Brais Martínez

35 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Brais Martínez United Kingdom 18 936 481 262 211 151 37 1.3k
Shaun Canavan United States 13 734 0.8× 680 1.4× 161 0.6× 93 0.4× 346 2.3× 53 1.3k
Michael Reale United States 11 993 1.1× 728 1.5× 170 0.6× 89 0.4× 286 1.9× 25 1.5k
Karan Sikka United States 13 576 0.6× 359 0.7× 80 0.3× 212 1.0× 83 0.5× 29 856
Minh Hoai Nguyen United States 14 451 0.5× 280 0.6× 82 0.3× 254 1.2× 113 0.7× 31 946
Matthew Pediaditis Greece 16 404 0.4× 367 0.8× 49 0.2× 174 0.8× 252 1.7× 36 1.1k
Bihan Jiang United Kingdom 7 874 0.9× 1.1k 2.3× 197 0.8× 218 1.0× 222 1.5× 9 1.4k
Christos Sagonas United Kingdom 10 1.7k 1.8× 215 0.4× 622 2.4× 169 0.8× 88 0.6× 14 2.0k
Miguel Bordallo López Finland 16 267 0.3× 212 0.4× 58 0.2× 78 0.4× 126 0.8× 70 754
Wen-Sheng Chu United States 16 1.2k 1.3× 835 1.7× 272 1.0× 267 1.3× 186 1.2× 26 1.5k
Sazali Yaacob Malaysia 20 248 0.3× 243 0.5× 262 1.0× 231 1.1× 469 3.1× 87 1.2k

Countries citing papers authored by Brais Martínez

Since Specialization
Citations

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

Fields of papers citing papers by Brais Martínez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brais Martínez

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

All Works

20 of 20 papers shown
1.
Bulat, Adrian, et al.. (2025). VladVA: Discriminative Fine-tuning of LVLMs. 4101–4111.
2.
Bulat, Adrian, et al.. (2024). Efficient Vision-Language pre-training via domain-specific learning for human activities. 7978–8000. 1 indexed citations
3.
Tan, Fuwen, Łukasz Dudziak, Shell Xu Hu, et al.. (2024). MobileQuant: Mobile-friendly Quantization for On-device Language Models. Edinburgh Research Explorer (University of Edinburgh). 9761–9771. 2 indexed citations
4.
Yang, Jing, Xiatian Zhu, Adrian Bulat, Brais Martínez, & Georgios Tzimiropoulos. (2024). Knowledge Distillation Meets Open-Set Semi-supervised Learning. International Journal of Computer Vision. 133(1). 315–334. 4 indexed citations
5.
Bulat, Adrian, Enrique Sánchez, Brais Martínez, & Georgios Tzimiropoulos. (2023). ReGen: A good Generative zero-shot video classifier should be Rewarded. 13477–13487.
6.
Derakhshani, Mohammad Mahdi, Enrique Sánchez, Adrian Bulat, et al.. (2023). Bayesian Prompt Learning for Image-Language Model Generalization. 15191–15200. 12 indexed citations
7.
Yang, Jing, Brais Martínez, Adrian Bulat, & Georgios Tzimiropoulos. (2021). Knowledge distillation via softmax regression representation learning. Queen Mary Research Online (Queen Mary University of London). 32 indexed citations
8.
Xu, Mengmeng, et al.. (2021). Low-Fidelity Video Encoder Optimization for Temporal Action Localization. Neural Information Processing Systems. 34. 13 indexed citations
9.
Bulat, Adrian, Brais Martínez, & Georgios Tzimiropoulos. (2021). High-Capacity Expert Binary Networks. Queen Mary Research Online (Queen Mary University of London). 16 indexed citations
10.
Martínez, Brais, Jing Yang, Adrian Bulat, & Georgios Tzimiropoulos. (2020). Training Binary Neural Networks with Real-to-Binary Convolutions. arXiv (Cornell University). 37 indexed citations
11.
Martínez, Brais, Michel Valstar, Bihan Jiang, & Maja Pantić. (2017). Automatic Analysis of Facial Actions: A Survey. IEEE Transactions on Affective Computing. 10(3). 325–347. 208 indexed citations
12.
Sánchez, Enrique, Georgios Tzimiropoulos, Brais Martínez, Fernando De la Torre, & Michel Valstar. (2017). A Functional Regression Approach to Facial Landmark Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(9). 2037–2050. 27 indexed citations
13.
Aung, Min Hane, Sebastian Kaltwang, Bernardino Romera‐Paredes, et al.. (2015). The Automatic Detection of Chronic Pain-Related Expression: Requirements, Challenges and the Multimodal EmoPain Dataset. IEEE Transactions on Affective Computing. 7(4). 435–451. 144 indexed citations
14.
Martínez, Brais & Maja Pantić. (2015). Facial landmarking for in-the-wild images with local inference based on global appearance. Image and Vision Computing. 36. 40–50. 3 indexed citations
15.
Martínez, Brais, et al.. (2013). Empirical analysis of cascade deformable models for multi-view face detection. University of Twente Research Information. 3 indexed citations
16.
Martínez, Brais, Michel Valstar, Xavier Binefa, & Maja Pantić. (2012). Local Evidence Aggregation for Regression-Based Facial Point Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(5). 1149–1163. 94 indexed citations
17.
Valstar, Michel, Brais Martínez, Xavier Binefa, & Maja Pantić. (2010). Facial point detection using boosted regression and graph models. University of Twente Research Information. 2729–2736. 214 indexed citations
18.
Martínez, Brais, et al.. (2006). Multiple Kernel Two-Step Tracking. 25. 2785–2788. 7 indexed citations
19.
Guitart, Raimón, et al.. (2005). Organochlorine Residues in Fishes from Two Rivers in Cantabria, Spain: Implications for a Program of Otter (Lutra lutra) Reintroduction. Bulletin of Environmental Contamination and Toxicology. 75(1). 143–148. 2 indexed citations
20.
Martínez, Brais, et al.. (1997). Drug points: Acute eosinophilic pneumonia associated with tenidap. BMJ. 314(7077). 349.1–349.1. 3 indexed citations

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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