Kaito Nakajima, Takafumi Katayama, Tian Song, Xiantao Jiang, T. Shimamoto
{"title":"基于视频游戏真实感增强的领域自适应语义分割","authors":"Kaito Nakajima, Takafumi Katayama, Tian Song, Xiantao Jiang, T. Shimamoto","doi":"10.1109/ICCE53296.2022.9730769","DOIUrl":null,"url":null,"abstract":"Unsupervised domain adaptation is considered as an effective technique to reduce the large amount supervised data. In order to solve this problem, unsupervised domain adaptation is considered to be an effective technique. In this work, three types of domain adaptation: image-level domain adaptation, inter-domain adaptation, and intra-domain adaptation are introduced to achieve better semantic segmentation accuracy. The proposed method achieved an mean IoU of 45.0%. Furthermore, by combining the proposed method with intra-domain adaptation, an mean IoU improvement of 1.2% is achieved compared to previous work.","PeriodicalId":350644,"journal":{"name":"2022 IEEE International Conference on Consumer Electronics (ICCE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Domain Adaptive Semantic Segmentation through Photorealistic Enhancement of Video Game\",\"authors\":\"Kaito Nakajima, Takafumi Katayama, Tian Song, Xiantao Jiang, T. Shimamoto\",\"doi\":\"10.1109/ICCE53296.2022.9730769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unsupervised domain adaptation is considered as an effective technique to reduce the large amount supervised data. In order to solve this problem, unsupervised domain adaptation is considered to be an effective technique. In this work, three types of domain adaptation: image-level domain adaptation, inter-domain adaptation, and intra-domain adaptation are introduced to achieve better semantic segmentation accuracy. The proposed method achieved an mean IoU of 45.0%. Furthermore, by combining the proposed method with intra-domain adaptation, an mean IoU improvement of 1.2% is achieved compared to previous work.\",\"PeriodicalId\":350644,\"journal\":{\"name\":\"2022 IEEE International Conference on Consumer Electronics (ICCE)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Consumer Electronics (ICCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE53296.2022.9730769\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Consumer Electronics (ICCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE53296.2022.9730769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Domain Adaptive Semantic Segmentation through Photorealistic Enhancement of Video Game
Unsupervised domain adaptation is considered as an effective technique to reduce the large amount supervised data. In order to solve this problem, unsupervised domain adaptation is considered to be an effective technique. In this work, three types of domain adaptation: image-level domain adaptation, inter-domain adaptation, and intra-domain adaptation are introduced to achieve better semantic segmentation accuracy. The proposed method achieved an mean IoU of 45.0%. Furthermore, by combining the proposed method with intra-domain adaptation, an mean IoU improvement of 1.2% is achieved compared to previous work.