{"title":"An Investigation on Sparsity of CapsNets for Adversarial Robustness","authors":"Lei Zhao, Lei Huang","doi":"10.1145/3475724.3483609","DOIUrl":null,"url":null,"abstract":"The routing-by-agreement mechanism in capsule networks (CapsNets) is used to build visual hierarchical relationships with a characteristic of assigning parts to wholes. The connections between capsules of different layers become sparser with more iterations of routing. This paper proposes techniques in measuring, controlling, and visualizing the sparsity of CapsNets. One essential observation in this paper is that the sparser CapsNets are possibly more robust to the adversarial attacks. We believe this observation will provide insights into designing more robust models.","PeriodicalId":279202,"journal":{"name":"Proceedings of the 1st International Workshop on Adversarial Learning for Multimedia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st International Workshop on Adversarial Learning for Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3475724.3483609","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 routing-by-agreement mechanism in capsule networks (CapsNets) is used to build visual hierarchical relationships with a characteristic of assigning parts to wholes. The connections between capsules of different layers become sparser with more iterations of routing. This paper proposes techniques in measuring, controlling, and visualizing the sparsity of CapsNets. One essential observation in this paper is that the sparser CapsNets are possibly more robust to the adversarial attacks. We believe this observation will provide insights into designing more robust models.