Mayu Otani

1.0k total citations
35 papers, 377 citations indexed

About

Mayu Otani is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Mayu Otani has authored 35 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 6 papers in Signal Processing. Recurrent topics in Mayu Otani's work include Multimodal Machine Learning Applications (14 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Video Analysis and Summarization (10 papers). Mayu Otani is often cited by papers focused on Multimodal Machine Learning Applications (14 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Video Analysis and Summarization (10 papers). Mayu Otani collaborates with scholars based in Japan, Finland and France. Mayu Otani's co-authors include Yuta Nakashima, Janne Heikkilä, Esa Rahtu, Chenhui Chu, Noa García, Shin’ichi Satoh, Zekun Yang, Haruo Takemura, Naoto Inoue and Kotaro Kikuchi and has published in prestigious journals such as IEEE Access, Neurocomputing and Computer Vision and Image Understanding.

In The Last Decade

Mayu Otani

31 papers receiving 361 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mayu Otani Japan	9	278	125	102	46	35	35	377
Kiron Lebeck United States	7	186 0.7×	52 0.4×	60 0.6×	98 2.1×	55 1.6×	9	358
Tim Lammarsch Austria	10	238 0.9×	94 0.8×	72 0.7×	16 0.3×	36 1.0×	17	279
Liang-Hua Chen Taiwan	11	363 1.3×	87 0.7×	73 0.7×	21 0.5×	14 0.4×	30	411
Jassim Happa United Kingdom	10	76 0.3×	63 0.5×	85 0.8×	122 2.7×	33 0.9×	35	318
Pengcheng Wang China	11	121 0.4×	125 1.0×	22 0.2×	24 0.5×	20 0.6×	37	294
Wasfi G. Al-Khatib Saudi Arabia	13	555 2.0×	306 2.4×	159 1.6×	26 0.6×	15 0.4×	32	739
Markus Höferlin Germany	11	302 1.1×	79 0.6×	66 0.6×	6 0.1×	26 0.7×	24	369
Simon Dobrišek Slovenia	11	205 0.7×	152 1.2×	130 1.3×	15 0.3×	7 0.2×	50	392
Toshiyuki Masui Japan	11	168 0.6×	69 0.6×	42 0.4×	57 1.2×	53 1.5×	24	330
Lauren Bradel United States	9	209 0.8×	86 0.7×	43 0.4×	13 0.3×	8 0.2×	13	249

Countries citing papers authored by Mayu Otani

Since Specialization

Citations

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

Fields of papers citing papers by Mayu Otani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mayu Otani

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Nakashima, Yuta, et al.. (2025). PixCon: Pixel-Level Contrastive Learning Revisited. Electronics. 14(8). 1623–1623.

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.

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

4.

Nakashima, Yuta, et al.. (2024). Unleashing the Power of Contrastive Learning for Zero-Shot Video Summarization. Journal of Imaging. 10(9). 229–229.

5.

Kikuchi, Kotaro, Naoto Inoue, Mayu Otani, Edgar Simo‐Serra, & Kota Yamaguchi. (2023). Generative Colorization of Structured Mobile Web Pages. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3639–3648. 5 indexed citations

6.

Otani, Mayu, et al.. (2023). Multimodal Color Recommendation in Vector Graphic Documents. 4003–4011. 1 indexed citations

7.

Inoue, Naoto, Kotaro Kikuchi, Edgar Simo‐Serra, Mayu Otani, & Kota Yamaguchi. (2023). Towards Flexible Multi-modal Document Models. 14287–14296. 5 indexed citations

8.

Wang, Xueting, et al.. (2023). Color Recommendation for Vector Graphic Documents based on Multi-Palette Representation. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3610–3618. 3 indexed citations

9.

Otani, Mayu, Yale Song, & Yang Wang. (2022). Video Summarization Overview. arXiv (Cornell University). 13(4). 284–335. 6 indexed citations

10.

Otani, Mayu, et al.. (2022). An Intelligent Color Recommendation Tool for Landing Page Design. 26–29. 6 indexed citations

11.

Yamada, Yutaro & Mayu Otani. (2022). Does Robustness on ImageNet Transfer to Downstream Tasks?. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9205–9214. 12 indexed citations

12.

Otani, Mayu, et al.. (2022). AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21044–21053.

13.

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

14.

Kato, Masahiro, et al.. (2021). Density-Ratio Based Personalised Ranking from Implicit Feedback. 3221–3233. 4 indexed citations

15.

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

16.

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

17.

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

18.

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

19.

Otani, Mayu, Yuta Nakashima, Esa Rahtu, & Janne Heikkilä. (2020). Uncovering Hidden Challenges in Query-Based Video Moment Retrieval. arXiv (Cornell University). 6 indexed citations

20.

Chu, Chenhui, Mayu Otani, & Yuta Nakashima. (2018). iParaphrasing: Extracting Visually Grounded Paraphrases via an Image. International Conference on Computational Linguistics. 3479–3492. 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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