{"title":"使用预先训练的面具佩戴者图像模型改进人脸识别","authors":"M. Hongo, T. Goto","doi":"10.1109/ICCCI51764.2021.9486820","DOIUrl":null,"url":null,"abstract":"Wearing a mask hides half of the face, making it difficult to recognize it as a face in computer vision. There is a problem that it becomes impossible to identify the whereabouts of a person or an individual because it is not recognized as a face. In this paper, we aim to improve the recognition rate by using learning-based method and combining both NVIDIA's pre-trained model and face images with and without masks.","PeriodicalId":180004,"journal":{"name":"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving Face Recognition Using Pre-trained Models for Mask Wearer Images\",\"authors\":\"M. Hongo, T. Goto\",\"doi\":\"10.1109/ICCCI51764.2021.9486820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wearing a mask hides half of the face, making it difficult to recognize it as a face in computer vision. There is a problem that it becomes impossible to identify the whereabouts of a person or an individual because it is not recognized as a face. In this paper, we aim to improve the recognition rate by using learning-based method and combining both NVIDIA's pre-trained model and face images with and without masks.\",\"PeriodicalId\":180004,\"journal\":{\"name\":\"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCI51764.2021.9486820\",\"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 3rd International Conference on Computer Communication and the Internet (ICCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCI51764.2021.9486820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving Face Recognition Using Pre-trained Models for Mask Wearer Images
Wearing a mask hides half of the face, making it difficult to recognize it as a face in computer vision. There is a problem that it becomes impossible to identify the whereabouts of a person or an individual because it is not recognized as a face. In this paper, we aim to improve the recognition rate by using learning-based method and combining both NVIDIA's pre-trained model and face images with and without masks.