{"title":"低延迟移动VR图形管道集成机器学习架构","authors":"Haomiao Jiang, Rohit Rao Padebettu, Kazuki Sakamoto, Behnam Bastani","doi":"10.1145/3355088.3365154","DOIUrl":null,"url":null,"abstract":"In this paper, we discuss frameworks to execute machine learning algorithms in the mobile VR graphics pipeline to improve performance and rendered image quality in real time. We analyze and compare the benefits and costs of various possibilities. We illustrate the strength of using machine framework in graphics pipeline with an application of efficient spatial temporal super-resolution that amplifies GPU render power to achieve better image quality.","PeriodicalId":435930,"journal":{"name":"SIGGRAPH Asia 2019 Technical Briefs","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Architecture of Integrated Machine Learning in Low Latency Mobile VR Graphics Pipeline\",\"authors\":\"Haomiao Jiang, Rohit Rao Padebettu, Kazuki Sakamoto, Behnam Bastani\",\"doi\":\"10.1145/3355088.3365154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we discuss frameworks to execute machine learning algorithms in the mobile VR graphics pipeline to improve performance and rendered image quality in real time. We analyze and compare the benefits and costs of various possibilities. We illustrate the strength of using machine framework in graphics pipeline with an application of efficient spatial temporal super-resolution that amplifies GPU render power to achieve better image quality.\",\"PeriodicalId\":435930,\"journal\":{\"name\":\"SIGGRAPH Asia 2019 Technical Briefs\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGGRAPH Asia 2019 Technical Briefs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3355088.3365154\",\"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 2019 Technical Briefs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3355088.3365154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Architecture of Integrated Machine Learning in Low Latency Mobile VR Graphics Pipeline
In this paper, we discuss frameworks to execute machine learning algorithms in the mobile VR graphics pipeline to improve performance and rendered image quality in real time. We analyze and compare the benefits and costs of various possibilities. We illustrate the strength of using machine framework in graphics pipeline with an application of efficient spatial temporal super-resolution that amplifies GPU render power to achieve better image quality.