Sundial-GAN: A Cascade Generative Adversarial Networks Framework for Deciphering Oracle Bone Inscriptions

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

3 Citations (SciVal)

Abstract

Oracle Bone Inscription (OBI) is an early hieroglyph in China, which is the most famous ancient writing system in the world. However, only a small number of OBI characters have been fully deciphered today. Chinese characters have different forms in different historical stages; therefore, it is very difficult to directly translate OBI characters to modern Chinese characters due to the long historic evolutionary process. In this paper, we propose a cascade generative adversarial networks (GAN) framework for deciphering OBI characters, named "Sundial-GAN", which is a cascaded structure to simulate Chinese characters' evolutionary process from an OBI character to its potential modern Chinese character. We select four representative stages in the evolutionary process of OBI, each of which is implemented by an individual GAN structure based on the characteristics of each evolutionary stage. These structures are cascaded in sequence to accurately simulate the Chinese characters' evolutionary process. For each input OBI character, Sundial-GAN can successfully generate the input's different forms at the four historical stages. Extensive experiments and comparisons demonstrate that generated characters at each stage have high similarities with real existing characters; therefore, the proposed method can significantly improve the efficiency and accuracy of OBI deciphering for archaeological researchers. Compared to direct image-to-image translation methods, our approach allows for a smoother translation process, a better grasp of details, and more effective avoiding random mappings in GANs.

Original languageEnglish
Title of host publicationMM 2022
Subtitle of host publicationProceedings of the 30th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages1195-1203
Number of pages9
ISBN (Electronic)9781450392037
DOIs
Publication statusPublished - 10 Oct 2022
Event30th ACM International Conference on Multimedia, MM 2022 - Lisboa, Portugal
Duration: 10 Oct 202214 Oct 2022

Publication series

NameMM 2022 - Proceedings of the 30th ACM International Conference on Multimedia

Conference

Conference30th ACM International Conference on Multimedia, MM 2022
Country/TerritoryPortugal
CityLisboa
Period10 Oct 202214 Oct 2022

Keywords

  • computational arts
  • end-to-end image translation
  • generative adversarial networks
  • oracle bone inscriptions deciphering

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