{"title":"神经网络环境遮挡","authors":"Daniel Holden, Jun Saito, T. Komura","doi":"10.1145/3005358.3005387","DOIUrl":null,"url":null,"abstract":"We present Neural Network Ambient Occlusion (NNAO), a fast, accurate screen space ambient occlusion algorithm that uses a neural network to learn an optimal approximation of the ambient occlusion effect. Our network is carefully designed such that it can be computed in a single pass allowing it to be used as a drop-in replacement for existing screen space ambient occlusion techniques.","PeriodicalId":242138,"journal":{"name":"SIGGRAPH ASIA 2016 Technical Briefs","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Neural network ambient occlusion\",\"authors\":\"Daniel Holden, Jun Saito, T. Komura\",\"doi\":\"10.1145/3005358.3005387\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present Neural Network Ambient Occlusion (NNAO), a fast, accurate screen space ambient occlusion algorithm that uses a neural network to learn an optimal approximation of the ambient occlusion effect. Our network is carefully designed such that it can be computed in a single pass allowing it to be used as a drop-in replacement for existing screen space ambient occlusion techniques.\",\"PeriodicalId\":242138,\"journal\":{\"name\":\"SIGGRAPH ASIA 2016 Technical Briefs\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGGRAPH ASIA 2016 Technical Briefs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3005358.3005387\",\"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 2016 Technical Briefs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3005358.3005387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present Neural Network Ambient Occlusion (NNAO), a fast, accurate screen space ambient occlusion algorithm that uses a neural network to learn an optimal approximation of the ambient occlusion effect. Our network is carefully designed such that it can be computed in a single pass allowing it to be used as a drop-in replacement for existing screen space ambient occlusion techniques.
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