{"title":"从英语到汉字的学习:基于《变形金刚》的书法艺术创作","authors":"Yifan Jin, Yi Zhang, Xi Yang","doi":"10.1145/3476124.3488642","DOIUrl":null,"url":null,"abstract":"We propose a transformer-based model to learn Square Word Calligraphy to write English words in the format of a square that resembles Chinese characters. To achieve this task, we compose a dataset by collecting the calligraphic characters created by artist Xu Bing, and labeling the position of each alphabet in the characters. Taking the input of English alphabets, we introduce a modified transformer-based model to learn the position relationship between each alphabet and predict the transformation parameters for each part to reassemble them as a Chinese character. We show the comparison results between our predicted characters and corresponding characters created by the artist to indicate our proposed model has a good performance on this task, and we also created new characters to show the “creativity” of our model.","PeriodicalId":199099,"journal":{"name":"SIGGRAPH Asia 2021 Posters","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Learning English to Chinese Character: Calligraphic Art Production based on Transformer\",\"authors\":\"Yifan Jin, Yi Zhang, Xi Yang\",\"doi\":\"10.1145/3476124.3488642\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a transformer-based model to learn Square Word Calligraphy to write English words in the format of a square that resembles Chinese characters. To achieve this task, we compose a dataset by collecting the calligraphic characters created by artist Xu Bing, and labeling the position of each alphabet in the characters. Taking the input of English alphabets, we introduce a modified transformer-based model to learn the position relationship between each alphabet and predict the transformation parameters for each part to reassemble them as a Chinese character. We show the comparison results between our predicted characters and corresponding characters created by the artist to indicate our proposed model has a good performance on this task, and we also created new characters to show the “creativity” of our model.\",\"PeriodicalId\":199099,\"journal\":{\"name\":\"SIGGRAPH Asia 2021 Posters\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGGRAPH Asia 2021 Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3476124.3488642\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGGRAPH Asia 2021 Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3476124.3488642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning English to Chinese Character: Calligraphic Art Production based on Transformer
We propose a transformer-based model to learn Square Word Calligraphy to write English words in the format of a square that resembles Chinese characters. To achieve this task, we compose a dataset by collecting the calligraphic characters created by artist Xu Bing, and labeling the position of each alphabet in the characters. Taking the input of English alphabets, we introduce a modified transformer-based model to learn the position relationship between each alphabet and predict the transformation parameters for each part to reassemble them as a Chinese character. We show the comparison results between our predicted characters and corresponding characters created by the artist to indicate our proposed model has a good performance on this task, and we also created new characters to show the “creativity” of our model.