{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/combating-the-elsagate-phenomenon-deep","title":"Combating the Elsagate phenomenon: Deep learning architectures for disturbing cartoons","arxiv_id":"1904.08910","date":"2019-04-18","proceeding":null,"authors":["Akari Ishikawa","Edson Bollis","Sandra Avila"],"abstract":"Watching cartoons can be useful for children's intellectual, social and\nemotional development. However, the most popular video sharing platform today\nprovides many videos with Elsagate content. Elsagate is a phenomenon that\ndepicts childhood characters in disturbing circumstances (e.g., gore, toilet\nhumor, drinking urine, stealing). Even with this threat easily available for\nchildren, there is no work in the literature addressing the problem. As the\nfirst to explore disturbing content in cartoons, we proceed from the most\nrecent pornography detection literature applying deep convolutional neural\nnetworks combined with static and motion information of the video. Our solution\nis compatible with mobile platforms and achieved 92.6% of accuracy. Our goal is\nnot only to introduce the first solution but also to bring up the discussion\naround Elsagate.","url_abs":"http://arxiv.org/abs/1904.08910v1","url_pdf":"http://arxiv.org/pdf/1904.08910v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"combating-the-elsagate-phenomenon-deep","repo_url":"https://github.com/akariueda/DLAforElsagate","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"pornography-detection","task_name":"Pornography Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}