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Significant bottlenecks exist in the field of multiview facial expression recognition (MFER) including a lack of high\u2010quality MFER datasets, and the limited model robustness in real\u2010world MFER scenarios. Therefore, this article first introduces a metahuman\u2010based MFER dataset (MMED), which effectively addresses the issues of insufficient quantity and quality in existing datasets. Second, a conditional cascade VGG (ccVGG) model is proposed, which can adaptively adjust expression feature extraction based on the input image's pose information. Finally, a hybrid training and few\u2010shot learning strategy are proposed that integrates our MMED dataset with a real\u2010world dataset and quickly deploys it in real\u2010world application scenarios using the proposed Meta\u2010Dist few\u2010shot learning method. Experiments on the Karolinska Directed Emotional Face (KDEF) dataset demonstrate that the proposed model exhibits improved robustness in multiview application scenarios and achieves a recognition accuracy improvement of 28.68% relative to the baseline. It demonstrates that the proposed MMED dataset can effectively improve the training efficiency of MFER models and facilitate easy deployment in real\u2010world applications. This work provides a reliable dataset for the MFER studies and paves the way for robust FER in any view for real\u2010world deployment.<\/jats:p>","DOI":"10.1002\/aisy.202300210","type":"journal-article","created":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T02:20:33Z","timestamp":1689819633000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["mFERMeta++ : Robust Multiview Facial Expression Recognition Based on Metahuman and Metalearning"],"prefix":"10.1002","volume":"5","author":[{"given":"Shuo","family":"Jiang","sequence":"first","affiliation":[{"name":"College of Electronics and Information Engineering Tongji University  Shanghai 201804 China"},{"name":"Frontiers Science Center for Intelligent Autonomous Systems  Shanghai 200120 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3155-6104","authenticated-orcid":false,"given":"Jiahang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering Tongji University  Shanghai 201804 China"},{"name":"Frontiers Science Center for Intelligent Autonomous Systems  Shanghai 200120 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanmin","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering Tongji University  Shanghai 201804 China"},{"name":"Frontiers Science Center for Intelligent Autonomous Systems  Shanghai 200120 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhipeng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering Tongji University  Shanghai 201804 China"},{"name":"Frontiers Science Center for Intelligent Autonomous Systems  Shanghai 200120 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3193-6269","authenticated-orcid":false,"given":"Bin","family":"He","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering Tongji University  Shanghai 201804 China"},{"name":"Frontiers Science Center for Intelligent Autonomous Systems  Shanghai 200120 China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,7,19]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"M. 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