{"url":"/dataset/raf-ml","name":"RAF-ML","full_name":"Real-world Affective Faces Multi Label","description_markdown":"Real-world Affective Faces Multi Label (RAF-ML) is a multi-label facial expression dataset with around 5K great-diverse facial images downloaded from the Internet with blended emotions and variability in subjects' identity, head poses, lighting conditions and occlusions. During annotation, 315 well-trained annotators are employed to ensure each image can be annotated enough independent times. And images with multi-peak label distribution are selected out to constitute the RAF-ML.\r\n\r\nRAF-ML provides 4908 number of real-world images with blended emotions, 6-dimensional expression distribution vector for each image, 5 accurate landmark locations and 37 automatic landmark locations, and baseline classifier outputs for multi-label emotion recognition.\r\n\r\nSource: [Real-world Affective Faces Multi Label](http://whdeng.cn/RAF/model2.html)","description_withheld":null,"homepage":"http://whdeng.cn/RAF/model2.html","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["RAF-ML"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}