{"url":"/dataset/mmi","name":"MMI","full_name":"MMI Facial Expression Database","description_markdown":"The **MMI** Facial Expression Database consists of over 2900 videos and high-resolution still images of 75 subjects. It is fully annotated for the presence of AUs in videos (event coding), and partially coded on frame-level, indicating for each frame whether an AU is in either the neutral, onset, apex or offset phase. A small part was annotated for audio-visual laughters.\r\n\r\nSource: [https://mmifacedb.eu/](https://mmifacedb.eu/)\r\nImage Source: [https://mmifacedb.eu/](https://mmifacedb.eu/)","description_withheld":null,"homepage":"https://mmifacedb.eu/","introduced_date":"2005-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Web-based database for facial expression analysis","first_author":null,"url":"https://doi.org/10.1109/ICME.2005.1521424"},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Facial Expression Recognition (FER)","url":"/task/facial-expression-recognition","datasets_with_task":"/datasets/task/facial-expression-recognition"}],"languages":[],"variants":["MMI"],"data_loaders":[],"num_papers_in_archive":65,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/facial-expression-recognition-on-mmi","task":"Facial Expression Recognition (FER)","dataset_variant":"MMI","rows":2,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"DeXpression","paper":"/paper/dexpression-deep-convolutional-neural-network","metrics":{"Accuracy":"98.63"},"code_links":[{"title":"MaxLikesMath/DeepLearningImplementations","url":"https://github.com/MaxLikesMath/DeepLearningImplementations"},{"title":"rdgozum/dexpression-pytorch","url":"https://github.com/rdgozum/dexpression-pytorch"},{"title":"ckapoor7/DeXpression","url":"https://github.com/ckapoor7/DeXpression"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/facial-motion-prior-networks-for-facial","title":"Facial Motion Prior Networks for Facial Expression Recognition","date":"2019-02-23","rows_on_this_dataset":1,"code_links":4,"syntology":null},{"paper":"/paper/dexpression-deep-convolutional-neural-network","title":"DeXpression: Deep Convolutional Neural Network for Expression Recognition","date":"2015-09-17","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}