{"url":"/dataset/ekman6","name":"Ekman6","full_name":null,"description_markdown":"the YF-E6 emotion dataset using the 6 basic emotion type as keywords on social video-sharing websites including YouTube and Flickr, leading to a total of 3000 videos. The dataset is labeled through crowdsourcing by 10 different annotators (5 males and 5 females), whose age ranged from 22 to 45. Annotators were given detailed definition for each emotion before performing the task. Every video is manually labeled by all the annotators. A video is excluded from the final dataset when over half of annotations are inconsistent with the initial search keyword.","description_withheld":null,"homepage":"","introduced_date":"2015-11-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/heterogeneous-knowledge-transfer-in-video","title":"Heterogeneous Knowledge Transfer in Video Emotion Recognition, Attribution and Summarization","first_author":"Baohan Xu","url":null},"license":{"name":"-","url":"http://yanweifu.github.io/Dataset.html"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Video Emotion Recognition","url":"/task/video-emotion-recognition","datasets_with_task":"/datasets/task/video-emotion-recognition"},{"name":"Video Emotion Detection","url":"/task/video-emotion-detection","datasets_with_task":"/datasets/task/video-emotion-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Ekman6"],"data_loaders":[],"num_papers_in_archive":11,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/video-emotion-recognition-on-ekman6","task":"Video Emotion Recognition","dataset_variant":"Ekman6","rows":6,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"VEMOCLAP","paper":"/paper/vemoclap-a-video-emotion-classification-web","metrics":{"Accuracy":"65.28"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/vemoclap-a-video-emotion-classification-web","title":"VEMOCLAP: A video emotion classification web application","date":"2024-10-22","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/weakly-supervised-video-emotion-detection-and","title":"Weakly Supervised Video Emotion Detection and Prediction via Cross-Modal Temporal Erasing Network","date":"2023-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/representation-learning-through-multimodal","title":"Representation Learning through Multimodal Attention and Time-Sync Comments for Affective Video Content Analysis","date":"2022-10-14","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/an-end-to-end-visual-audio-attention-network","title":"An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos","date":"2020-02-12","rows_on_this_dataset":1,"code_links":0,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":4,"samples_unverified":3,"pointer_only_for_licence":7,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/heterogeneous-knowledge-transfer-in-video","title":"Heterogeneous Knowledge Transfer in Video Emotion Recognition, Attribution and Summarization","date":"2015-11-16","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":7,"samples_ran":4,"samples_unverified":3,"pointer_only_for_licence":7,"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."}