W. Chu, I. Ide, Naoko Nitta, N. Tsumura, T. Yamasaki
{"title":"MMArt-ACM'20: International Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia 2020","authors":"W. Chu, I. Ide, Naoko Nitta, N. Tsumura, T. Yamasaki","doi":"10.1145/3372278.3388042","DOIUrl":null,"url":null,"abstract":"The International Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia (MMArt-ACM) solicits contributions on methodology advancement and novel applications of multimedia artworks and attractiveness computing that emerge in the era of big data and deep learning. Despite the strike of the Covid-19 pandemic, this workshop attracts submissions of diverse topics in these two fields, and the workshop program finally consists of five presented papers. The topics cover image retrieval, image transformation and generation, recommendation system, and image/video summarization. The actual MMArt-ACM'20 Proceedings are available in the ACM DL at: https://dl.acm.org/citation.cfm?id=3379173","PeriodicalId":158014,"journal":{"name":"Proceedings of the 2020 International Conference on Multimedia Retrieval","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 International Conference on Multimedia Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3372278.3388042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The International Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia (MMArt-ACM) solicits contributions on methodology advancement and novel applications of multimedia artworks and attractiveness computing that emerge in the era of big data and deep learning. Despite the strike of the Covid-19 pandemic, this workshop attracts submissions of diverse topics in these two fields, and the workshop program finally consists of five presented papers. The topics cover image retrieval, image transformation and generation, recommendation system, and image/video summarization. The actual MMArt-ACM'20 Proceedings are available in the ACM DL at: https://dl.acm.org/citation.cfm?id=3379173