{"title":"基于stylegan的剪贴引导图像形状操作","authors":"Yuchen Qian, Kohei Yamamoto, Keiji Yanai","doi":"10.1145/3549555.3549556","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a text-guided image manipulation method which focuses on editing shape attribute using text description. We combine an image generation model, StyleGAN2, and image-text matching model, CLIP, and we have achieved the goal of image shape attribute manipulation by modifying the parameters of the pretrained StyleGAN2 generator. Qualitative and quantitative evaluations are conducted to demonstrate the effectiveness of the proposed method.","PeriodicalId":191591,"journal":{"name":"Proceedings of the 19th International Conference on Content-based Multimedia Indexing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"StyleGAN-based CLIP-guided Image Shape Manipulation\",\"authors\":\"Yuchen Qian, Kohei Yamamoto, Keiji Yanai\",\"doi\":\"10.1145/3549555.3549556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a text-guided image manipulation method which focuses on editing shape attribute using text description. We combine an image generation model, StyleGAN2, and image-text matching model, CLIP, and we have achieved the goal of image shape attribute manipulation by modifying the parameters of the pretrained StyleGAN2 generator. Qualitative and quantitative evaluations are conducted to demonstrate the effectiveness of the proposed method.\",\"PeriodicalId\":191591,\"journal\":{\"name\":\"Proceedings of the 19th International Conference on Content-based Multimedia Indexing\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 19th International Conference on Content-based Multimedia Indexing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3549555.3549556\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 19th International Conference on Content-based Multimedia Indexing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3549555.3549556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a text-guided image manipulation method which focuses on editing shape attribute using text description. We combine an image generation model, StyleGAN2, and image-text matching model, CLIP, and we have achieved the goal of image shape attribute manipulation by modifying the parameters of the pretrained StyleGAN2 generator. Qualitative and quantitative evaluations are conducted to demonstrate the effectiveness of the proposed method.