Ankit Phogat, Matthew Fisher, D. Kaufman, Vineet Batra
{"title":"皮肤矢量图形与gan","authors":"Ankit Phogat, Matthew Fisher, D. Kaufman, Vineet Batra","doi":"10.1145/3306214.3338544","DOIUrl":null,"url":null,"abstract":"We propose a novel method for editing vector graphics which enables users to intuitively modify complex Bézier geometry. Our method uses a Generative Adversarial Network (GAN) to automatically predict salient points for any arbitrary geometry defined by cubic Bézier curves, which are used as handle locations for a Linear Blend Skinning transformation. Further, we bind input geometry to a triangle mesh, to decouple the complexity of input geometry from mesh topology. Finally, to reconstruct Bézier curves from the transformed mesh, we formulate a linear optimization problem and solve it in performant manner to ensure real time feedback, without increasing the number of Bézier segments.","PeriodicalId":216038,"journal":{"name":"ACM SIGGRAPH 2019 Posters","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Skinning vector graphics with GANs\",\"authors\":\"Ankit Phogat, Matthew Fisher, D. Kaufman, Vineet Batra\",\"doi\":\"10.1145/3306214.3338544\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel method for editing vector graphics which enables users to intuitively modify complex Bézier geometry. Our method uses a Generative Adversarial Network (GAN) to automatically predict salient points for any arbitrary geometry defined by cubic Bézier curves, which are used as handle locations for a Linear Blend Skinning transformation. Further, we bind input geometry to a triangle mesh, to decouple the complexity of input geometry from mesh topology. Finally, to reconstruct Bézier curves from the transformed mesh, we formulate a linear optimization problem and solve it in performant manner to ensure real time feedback, without increasing the number of Bézier segments.\",\"PeriodicalId\":216038,\"journal\":{\"name\":\"ACM SIGGRAPH 2019 Posters\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SIGGRAPH 2019 Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3306214.3338544\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGGRAPH 2019 Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3306214.3338544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We propose a novel method for editing vector graphics which enables users to intuitively modify complex Bézier geometry. Our method uses a Generative Adversarial Network (GAN) to automatically predict salient points for any arbitrary geometry defined by cubic Bézier curves, which are used as handle locations for a Linear Blend Skinning transformation. Further, we bind input geometry to a triangle mesh, to decouple the complexity of input geometry from mesh topology. Finally, to reconstruct Bézier curves from the transformed mesh, we formulate a linear optimization problem and solve it in performant manner to ensure real time feedback, without increasing the number of Bézier segments.