{"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/mead-a-large-scale-audio-visual-dataset-for","title":"MEAD: A Large-scale Audio-visual Dataset for Emotional Talking-face Generation","arxiv_id":null,"date":"2020-08-01","proceeding":"ECCV 2020 8","authors":["Kaisiyuan Wang Qianyi Wu Linsen Song Zhuoqian Yang Wayne Wu Chen Qian Ran He Yu Qiao Chen Change Loy"],"abstract":"The synthesis of natural emotional reactions is an essentialcriteria in vivid talking-face video generation. This criteria is nevertheless seldom taken into consideration in previous works due to the absence of a large-scale, high-quality emotional audio-visual dataset. To address this issue, we build the Multi-view Emotional Audio-visual Dataset(MEAD) which is a talking-face video corpus featuring 60 actors and actresses talking with 8 different emotions at 3 different intensity levels. High-quality audio-visual clips are captured at 7 different view angles in a strictly-controlled environment. Together with the dataset, we release an emotional talking-face generation baseline which enables the manipulation of both emotion and its intensity. Our dataset will be made public and could benefit a number of different research fields including conditional generation, cross-modal understanding and expression recognition.","url_abs":"https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3837_ECCV_2020_paper.php","url_pdf":"https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123660698.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":"mead-a-large-scale-audio-visual-dataset-for","repo_url":"https://github.com/uniBruce/Mead","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"face-generation","task_name":"Face Generation"},{"task_slug":"talking-face-generation","task_name":"Talking Face Generation"},{"task_slug":"talking-head-generation","task_name":"Talking Head Generation"},{"task_slug":"video-generation","task_name":"Video Generation"}],"methods":[],"datasets_introduced":[{"slug":"mead","name":"MEAD","full_name":"A Large-scale Audio-visual Dataset for Emotional Talking-face Generation"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}