Noa García

773 total citations
28 papers, 275 citations indexed

About

Noa García is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Noa García has authored 28 papers receiving a total of 275 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 6 papers in Cognitive Neuroscience. Recurrent topics in Noa García's work include Multimodal Machine Learning Applications (18 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Noa García is often cited by papers focused on Multimodal Machine Learning Applications (18 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Noa García collaborates with scholars based in Japan, France and United Kingdom. Noa García's co-authors include Yuta Nakashima, Mayu Otani, Chenhui Chu, George Vogiatzis, Haruo Takemura, Zekun Yang, Yuta Nakashima, Benjamin Renoust, Yusuke Hirota and Zechen Bai and has published in prestigious journals such as IEEE Access, Neurocomputing and Image and Vision Computing.

In The Last Decade

Noa García

25 papers receiving 265 citations

Peers

Noa García

CVPR

AI

CN

SR

SP

Nouha Dziri United States

Negar Rostamzadeh United States

Shauli Ravfogel Israel

Brian Dolhansky United States

Joanna Bitton Canada

Alicia Parrish United States

Andrea Vanzo Italy

Stella Frank United Kingdom

Prithviraj Ammanabrolu United States

Ivan Donadello Italy

Nouha Dziri United States

Noa García

64 ×0.3

CVPR

252 ×2.1

AI

9 ×0.5

CN

14 ×0.8

SR

19 ×1.4

SP

Citations per year, relative to Noa García Noa García (= 1×) peers Nouha Dziri

Countries citing papers authored by Noa García

Since Specialization

Citations

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

Fields of papers citing papers by Noa García

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noa García

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

All Works

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20 of 20 papers shown

1.

Nakashima, Yuta, et al.. (2025). Revealing Gender Bias from Prompt to Image in Stable Diffusion. Journal of Imaging. 11(2). 35–35. 1 indexed citations

2.

García, Noa, et al.. (2024). A Picture May Be Worth a Hundred Words for Visual Question Answering. Electronics. 13(21). 4290–4290. 1 indexed citations

3.

Nakashima, Yuta, et al.. (2024). Stable Diffusion Exposed: Gender Bias from Prompt to Image. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 7. 1648–1659. 1 indexed citations

4.

Hirota, Yusuke, et al.. (2024). Would Deep Generative Models Amplify Bias in Future Models?. 10833–10843. 4 indexed citations

5.

Nakashima, Yuta, et al.. (2024). Auditing Image-based NSFW Classifiers for Content Filtering. 1163–1173.

6.

García, Noa, et al.. (2024). Exploring Emotional Stimuli Detection in Artworks: A Benchmark Dataset and Baselines Evaluation. Journal of Imaging. 10(6). 136–136.

7.

García, Noa, et al.. (2024). Situating the social issues of image generation models in the model life cycle: a sociotechnical approach. AI and Ethics. 5(2). 1769–1786. 8 indexed citations

8.

Nakashima, Yuta, et al.. (2024). Reproducibility Companion Paper: Stable Diffusion for Content-Style Disentanglement in Art Analysis. 1228–1231.

9.

Nakashima, Yuta, et al.. (2024). GOYA: Leveraging Generative Art for Content-Style Disentanglement. Journal of Imaging. 10(7). 156–156. 2 indexed citations

10.

García, Noa, et al.. (2024). Retrieving Emotional Stimuli in Artworks. 515–523. 1 indexed citations

11.

García, Noa, et al.. (2023). Uncurated Image-Text Datasets: Shedding Light on Demographic Bias. 6957–6966. 19 indexed citations

12.

Hirota, Yusuke, Yuta Nakashima, & Noa García. (2022). Gender and Racial Bias in Visual Question Answering Datasets. arXiv (Cornell University). 1280–1292. 18 indexed citations

13.

García, Noa, et al.. (2021). Transferring Domain-Agnostic Knowledge in Video Question Answering. 2 indexed citations

14.

Yang, Zekun, Noa García, Chenhui Chu, et al.. (2021). A comparative study of language transformers for video question answering. Neurocomputing. 445. 121–133. 17 indexed citations

15.

Yang, Zekun, Mayu Otani, Noa García, et al.. (2021). The Laughing Machine: Predicting Humor in Video. 2072–2081. 9 indexed citations

16.

Samaran, Jules, Noa García, Mayu Otani, Chenhui Chu, & Yuta Nakashima. (2021). Attending Self-Attention: A Case Study of Visually Grounded Supervision in Vision-and-Language Transformers. 81–86. 1 indexed citations

17.

García, Noa, Mayu Otani, Chenhui Chu, et al.. (2021). Visual Question Answering with Textual Representations for Images. 3147–3150. 3 indexed citations

18.

Yang, Zekun, Noa García, Chenhui Chu, et al.. (2020). BERT Representations for Video Question Answering. OUKA (Osaka University Knowledge Archive) (Osaka University). 1545–1554. 59 indexed citations

19.

García, Noa & George Vogiatzis. (2018). Asymmetric Spatio-Temporal Embeddings for Large-Scale Image-to-Video Retrieval. Aston Publications Explorer (Aston University). 206. 2 indexed citations

20.

García, Noa. (2018). Temporal Aggregation of Visual Features for Large-Scale Image-to-Video Retrieval. 489–492. 6 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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