{"url":"/dataset/emotic","name":"EMOTIC","full_name":"EMOTIons in Context","description_markdown":"The EMOTIC dataset, named after EMOTions In Context, is a database of images with people in real environments, annotated with their apparent emotions. The images are annotated with an extended list of 26 emotion categories combined with the three common continuous dimensions Valence, Arousal and Dominance.\r\n\r\nSource: [Context Based Emotion Recognition using EMOTIC Dataset](https://arxiv.org/abs/2003.13401)","description_withheld":null,"homepage":"https://github.com/rkosti/emotic","introduced_date":"2020-03-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/context-based-emotion-recognition-using","title":"Context Based Emotion Recognition using EMOTIC Dataset","first_author":"Ronak Kosti","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Action Recognition","url":"/task/action-recognition-in-videos","datasets_with_task":"/datasets/task/action-recognition-in-videos"},{"name":"Emotion Recognition","url":"/task/emotion-recognition","datasets_with_task":"/datasets/task/emotion-recognition"},{"name":"Multimodal Emotion Recognition","url":"/task/multimodal-emotion-recognition","datasets_with_task":"/datasets/task/multimodal-emotion-recognition"},{"name":"Emotion Recognition in Context","url":"/task/emotion-recognition-in-context","datasets_with_task":"/datasets/task/emotion-recognition-in-context"},{"name":"Arousal Estimation","url":"/task/arousal-estimation","datasets_with_task":"/datasets/task/arousal-estimation"},{"name":"Valence Estimation","url":"/task/valence-estimation","datasets_with_task":"/datasets/task/valence-estimation"},{"name":"Dominance Estimation","url":"/task/dominance-estimation","datasets_with_task":"/datasets/task/dominance-estimation"},{"name":"Age Classification","url":"/task/age-classification","datasets_with_task":"/datasets/task/age-classification"}],"languages":[],"variants":["EMOTIC"],"data_loaders":[{"repo":"https://github.com/rkosti/emotic","url":"https://github.com/rkosti/emotic","frameworks":["pytorch"]}],"num_papers_in_archive":38,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/emotion-recognition-in-context-on-emotic","task":"Emotion Recognition in Context","dataset_variant":"EMOTIC","rows":9,"metrics":["mAP"],"first_row_in_archive_order":{"model":"A. Xenos et al","paper":"/paper/vllms-provide-better-context-for-emotion","metrics":{"mAP":"38.52"},"code_links":[{"title":"nickyfot/emocommonsense","url":"https://github.com/nickyfot/emocommonsense"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/emotion-recognition-on-emotic","task":"Emotion Recognition","dataset_variant":"EMOTIC","rows":2,"metrics":["Top-3 Accuracy (%)"],"first_row_in_archive_order":{"model":"CAGE","paper":"/paper/cage-circumplex-affect-guided-expression","metrics":{"Top-3 Accuracy (%)":"14.73"},"code_links":[{"title":"wagner-niklas/cage_expression_inference","url":"https://github.com/wagner-niklas/cage_expression_inference"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/cage-circumplex-affect-guided-expression","title":"CAGE: Circumplex Affect Guided Expression Inference","date":"2024-04-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/vllms-provide-better-context-for-emotion","title":"VLLMs Provide Better Context for Emotion Understanding Through Common Sense Reasoning","date":"2024-04-10","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/focusclip-multimodal-subject-level-guidance","title":"Human Pose Descriptions and Subject-Focused Attention for Improved Zero-Shot Transfer in Human-Centric Classification Tasks","date":"2024-03-11","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/learning-emotion-representations-from-verbal-1","title":"Learning Emotion Representations from Verbal and Nonverbal Communication","date":"2023-05-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":29,"samples_ran":10,"samples_unverified":19,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/context-based-emotion-recognition-using","title":"Context Based Emotion Recognition using EMOTIC Dataset","date":"2020-03-30","rows_on_this_dataset":3,"code_links":3,"syntology":null},{"paper":"/paper/emoticon-context-aware-multimodal-emotion","title":"EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege's Principle","date":"2020-03-14","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/context-aware-emotion-recognition-networks","title":"Context-Aware Emotion Recognition Networks","date":"2019-08-16","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":29,"samples_ran":10,"samples_unverified":19,"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."}