Abstract

The scripts used for calligraphic works are roughly divided into five scripts, Seal, Clerical, Cursive, Running, and Standard. And many of these require specialized knowledge for reading. This method provides image recognition and transformation to support the appreciation of calligraphic works. I treated the former as my thesis and now I am working on the latter.

 

Members

NameAffiliationWeb site
Shohei NinomiyaKeio University
Masanori NakayamaKeio University
Atsushi MiyazawaKeio University

Video

demo video (×2)

Publications

Journals

  1. Shohei Ninomiya, Issei Fujishiro: “Caps: Script Conversion in Calligraphic Works Using Deep Learning―Recognition of seal script characters and generation of running script works―,” The Journal of the Society for Art and Science, Vol. 21, No. 1, pp. 11ー22, March 30, 2022, doi: 10.3756/artsci.21.11 (in Japanese).

Conferences

  1. Shohei Ninomiya, Issei Fujishiro: “Script Conversion in Calligraphic Works Using Deep Learning―Recognition of seal script characters and generation of running script works―,” in Proceedings of The Society for Art and Science NICOGRAPH 2021, pp. F-8:1―F-8:8, November 5―8, 2021, Student Encouragement Award (in Japanese).

Presentations

Domestic presentations

  1. Shohei Ninomiya, Issei Fujishiro: “Script Conversion in Calligraphic Works Using Deep Learning―Generation of running script works―,” in ADADA Japan 7th annual conference, No. 20, Online, October 8, 2021, Student Encouragement Award (in Japanese).
  2. Shohei Ninomiya, Masanori Nakayama, Atsushi Miyazawa, Issei Fujishiro: “Toward script translation in calligraphic works using deep learning: Character recognition of seal scripts,” in The Technical Report of the Institute of Image Information and Television Engineers, Vol. 44, No. 10, pp. 75―78, March, 2020, Excellent Research Presentation Award (in Japanese).
  3. Shohei Ninomiya, Masanori Nakayama, Atsushi Miyazawa, Issei Fujishiro: “Script translation in calligraphic works using deep learning,” in Proceedings of the 82th National Convention of International Processing Society of Japan, Vol. 4, pp. 135―136 (2ZC-04), Kanazawa University Ohgigaoka Campus, Ishikawa, Online, March 5―7, 2020, Student Encouragement Award (in Japanese).

Grants

  1. Grant-in-Aid for Scientific Research (A): 17H00737 (2019―2021), 21H04916 (2021―2022)

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