Contents Science Lab

News

November 10, 2020: Our work on Imageability estimation using visual and language features by C. Matsuhira et al. got presented at ICMR2020.

October 16, 2020: Our work on sentence imageability-aware image captioning by K. Umemura et al. got accepted by MMM2021.

April 1, 2020: Contents Science Lab was established.

Recent projects

Book page colorization based on perception

In this research, we colorize pages of books according to human perception in order to summarize and compare book contents.



Image captioning considering imageability

In this research, we incorporate psycholinguistics into image captioning in order to tailor captions to different applications.



Imageability estimation

In this research, we model the human perception of the semantic gap for use in affective computing.



Mimetic words

In this research, we analyze the phonetic characteristics and human perception of mimetic words used in Japanese to describe human gait.

Recent publications

Feature Extraction for Claim Check-Worthiness Prediction Tasks Using LLM. Yuka Teramoto, Takahiro Komamizu, Mitsunori Matsushita, Kenji Hatano. The 26th International Conference on Information Integration and Web Intelligence (iiWAS2024), pp.53-58, December 2024.

Action Selection Learning for Multi-label Multi-view Action Recognition. Trung Thanh Nguyen, Yasutomo Kawanishi, Takahiro Komamizu, Ichiro Ide. ACM Multimedia Asia 2024, pp.1-8, December 2024.

ACM Multimedia 2024 参加報告. 松平 茅隼. DBSJ Newsletter, 17(7), 3, December 2024.

Cross-modal recipe retrieval based on unified text encoder with fine-grained contrastive learning. Bolin Zhang, Haruya Kyutoku, Keisuke Doman, Takahiro Komamizu, Ichiro Ide, Jiangbo Qian. Knowledge-Based Systems, 305(112641), pp.1-15, December 2024.

名古屋大学におけるデジタル人材育成に向けたリカレント教育プログラムの取り組み. 駒水孝裕. 令和6年度東海地区大学教育研究会 研究大会：「地域社会のニーズとリカレント教育のこれから」～豊かに、そして幸せに生きるために～, November 2024.

名古屋大学における学部レベルのデータ科学教育. 井手 一郎. 2024年度数理・データサイエンス・AI教育強化拠点コンソーシアム東海ブロック会議, November 2024.

Investigating Conceptual Blending of a Diffusion Model for Improving Nonword-to-Image Generation. Chihaya Matsuhira, Marc A. Kastner, Takahiro Komamizu, Takatsugu Hirayama, Ichiro Ide. Proceedings of the 32nd ACM International Conference on Multimedia (ACMMM), pp.7307-7315, October 2024.

Towards the understanding of human perception through generative AI technology. Ichiro Ide. International Symposium on Advanced and Sustainable Science and Technology (ISASST) 2024, September 2024.

大規模言語モデルは未知語に対する人間の感情想起を再現できるか？. 宮川由衣, 松平 茅隼, 加藤 大貴, 平山 高嗣, 駒水孝裕, 井手 一郎. テキストアナリティクス・シンポジウム, September 2024.

R-DiP: Re-ranking Based Diffusion Pre-computation for Image Retrieval. Tatsuya Kato, Takahiro Komamizu, Ichiro Ide. The 35th International Conference on Database and Expert Systems Applications (DEXA 2024), pp.233-247, August 2024.