{"title":"使用图像到图像转换的引导图像风化","authors":"Li-Yu Chen, I-Chao Shen, Bing-Yu Chen","doi":"10.1145/3478512.3488603","DOIUrl":null,"url":null,"abstract":"In this paper, we present a guided image weathering method that allows the user to generate the weathering process. The core of our method is a three-step method to generate textures at different time steps of the weathering process. The input texture is analyzed first to obtain the weathering degree (age map) for each pixel, then we train a conditional adversarial network to generate texture patches with diverse weathering effects. Once the training is finished, new weathering results can be generated by manipulating the age map, such as automatic interpolation and manually modified by the user.","PeriodicalId":156290,"journal":{"name":"SIGGRAPH Asia 2021 Technical Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Guided Image Weathering using Image-to-Image Translation\",\"authors\":\"Li-Yu Chen, I-Chao Shen, Bing-Yu Chen\",\"doi\":\"10.1145/3478512.3488603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a guided image weathering method that allows the user to generate the weathering process. The core of our method is a three-step method to generate textures at different time steps of the weathering process. The input texture is analyzed first to obtain the weathering degree (age map) for each pixel, then we train a conditional adversarial network to generate texture patches with diverse weathering effects. Once the training is finished, new weathering results can be generated by manipulating the age map, such as automatic interpolation and manually modified by the user.\",\"PeriodicalId\":156290,\"journal\":{\"name\":\"SIGGRAPH Asia 2021 Technical Communications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGGRAPH Asia 2021 Technical Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3478512.3488603\",\"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 Technical Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3478512.3488603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Guided Image Weathering using Image-to-Image Translation
In this paper, we present a guided image weathering method that allows the user to generate the weathering process. The core of our method is a three-step method to generate textures at different time steps of the weathering process. The input texture is analyzed first to obtain the weathering degree (age map) for each pixel, then we train a conditional adversarial network to generate texture patches with diverse weathering effects. Once the training is finished, new weathering results can be generated by manipulating the age map, such as automatic interpolation and manually modified by the user.