Joseph P. Robinson, Ming Shao, Handong Zhao, Yue Wu, Timothy Gillis, Y. Fu
{"title":"识别野外家庭(RFIW):与ACM MM 2017联合举办的数据挑战研讨会","authors":"Joseph P. Robinson, Ming Shao, Handong Zhao, Yue Wu, Timothy Gillis, Y. Fu","doi":"10.1145/3134421.3134424","DOIUrl":null,"url":null,"abstract":"Recognizing Families In the Wild (RFIW) is a large-scale, multi-track automatic kinship recognition evaluation, supporting both kinship verification and family classification on scales much larger than ever before. It was organized as a Data Challenge Workshop hosted in conjunction with ACM Multimedia 2017. This was achieved with the largest image collection that supports kin-based vision tasks. In the end, we use this manuscript to summarize evaluation protocols, progress made and some technical background and performance ratings of the algorithms used, and a discussion on promising directions for both research and engineers to be taken next in this line of work.","PeriodicalId":209776,"journal":{"name":"Proceedings of the 2017 Workshop on Recognizing Families In the Wild","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"Recognizing Families In the Wild (RFIW): Data Challenge Workshop in conjunction with ACM MM 2017\",\"authors\":\"Joseph P. Robinson, Ming Shao, Handong Zhao, Yue Wu, Timothy Gillis, Y. Fu\",\"doi\":\"10.1145/3134421.3134424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recognizing Families In the Wild (RFIW) is a large-scale, multi-track automatic kinship recognition evaluation, supporting both kinship verification and family classification on scales much larger than ever before. It was organized as a Data Challenge Workshop hosted in conjunction with ACM Multimedia 2017. This was achieved with the largest image collection that supports kin-based vision tasks. In the end, we use this manuscript to summarize evaluation protocols, progress made and some technical background and performance ratings of the algorithms used, and a discussion on promising directions for both research and engineers to be taken next in this line of work.\",\"PeriodicalId\":209776,\"journal\":{\"name\":\"Proceedings of the 2017 Workshop on Recognizing Families In the Wild\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 Workshop on Recognizing Families In the Wild\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3134421.3134424\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 Workshop on Recognizing Families In the Wild","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3134421.3134424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognizing Families In the Wild (RFIW): Data Challenge Workshop in conjunction with ACM MM 2017
Recognizing Families In the Wild (RFIW) is a large-scale, multi-track automatic kinship recognition evaluation, supporting both kinship verification and family classification on scales much larger than ever before. It was organized as a Data Challenge Workshop hosted in conjunction with ACM Multimedia 2017. This was achieved with the largest image collection that supports kin-based vision tasks. In the end, we use this manuscript to summarize evaluation protocols, progress made and some technical background and performance ratings of the algorithms used, and a discussion on promising directions for both research and engineers to be taken next in this line of work.