{"title":"基于残差增强网络的逼真人脸素描-照片合成","authors":"Weiguo Wan, Yong Yang, Wei Tu","doi":"10.1109/ICCEAI52939.2021.00037","DOIUrl":null,"url":null,"abstract":"Face sketch-photo synthesis is a significant challenge task in computer vision area, due to the blurred facial details and color distortion produced by the existing approaches. In this paper, we propose a realistic face sketch-photo synthesis method based on residual enhancement network. In the network, a residual enhancement module is constructed and embedded in U-Net to improve the feature representation capability of the deep network. In addition, a detail loss and a perception loss are adopted to constrain the synthesized image has abundant detail and realistic photo style. Experimental results on multiple face sketch datasets indicate that the proposed method obtains superior performance than the state-of-the-art methods, both in terms of visual perception and objective evaluations.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Residual Enhancement Network for Realistic Face Sketch-Photo Synthesis\",\"authors\":\"Weiguo Wan, Yong Yang, Wei Tu\",\"doi\":\"10.1109/ICCEAI52939.2021.00037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Face sketch-photo synthesis is a significant challenge task in computer vision area, due to the blurred facial details and color distortion produced by the existing approaches. In this paper, we propose a realistic face sketch-photo synthesis method based on residual enhancement network. In the network, a residual enhancement module is constructed and embedded in U-Net to improve the feature representation capability of the deep network. In addition, a detail loss and a perception loss are adopted to constrain the synthesized image has abundant detail and realistic photo style. Experimental results on multiple face sketch datasets indicate that the proposed method obtains superior performance than the state-of-the-art methods, both in terms of visual perception and objective evaluations.\",\"PeriodicalId\":331409,\"journal\":{\"name\":\"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEAI52939.2021.00037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEAI52939.2021.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Residual Enhancement Network for Realistic Face Sketch-Photo Synthesis
Face sketch-photo synthesis is a significant challenge task in computer vision area, due to the blurred facial details and color distortion produced by the existing approaches. In this paper, we propose a realistic face sketch-photo synthesis method based on residual enhancement network. In the network, a residual enhancement module is constructed and embedded in U-Net to improve the feature representation capability of the deep network. In addition, a detail loss and a perception loss are adopted to constrain the synthesized image has abundant detail and realistic photo style. Experimental results on multiple face sketch datasets indicate that the proposed method obtains superior performance than the state-of-the-art methods, both in terms of visual perception and objective evaluations.