{"url":"/dataset/merl-rav-dataset","name":"MERL-RAV","full_name":"MERL Reannotation of AFLW with Visibility","description_markdown":"The MERL-RAV (MERL Reannotation of AFLW with Visibility) Dataset contains over 19,000 face images in a full range of head poses. Each face is manually labeled with the ground-truth locations of 68 landmarks, with the additional information of whether each landmark is unoccluded, self-occluded (due to extreme head poses), or externally occluded. The images were annotated by professional labelers, supervised by researchers at Mitsubishi Electric Research Laboratories (MERL).","description_withheld":null,"homepage":"https://github.com/abhi1kumar/MERL-RAV_dataset","introduced_date":"2020-07-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/luvli-face-alignment-estimating-landmarks","title":"LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood","first_author":"Abhinav Kumar","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"Face Alignment","url":"/task/face-alignment","datasets_with_task":"/datasets/task/face-alignment"}],"languages":[],"variants":["MERL-RAV"],"data_loaders":[{"repo":"https://github.com/abhi1kumar/MERL-RAV_dataset","url":"https://github.com/abhi1kumar/MERL-RAV_dataset","frameworks":[]}],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/face-alignment-on-merl-rav","task":"Face Alignment","dataset_variant":"MERL-RAV","rows":2,"metrics":["NME (box)","AUC@7 (box) "],"first_row_in_archive_order":{"model":"SPIGA","paper":"/paper/shape-preserving-facial-landmarks-with-graph","metrics":{"AUC@7 (box) ":"78.47","NME (box)":"1.51"},"code_links":[{"title":"andresprados/spiga","url":"https://github.com/andresprados/spiga"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/pose-estimation-on-merl-rav","task":"Pose Estimation","dataset_variant":"MERL-RAV","rows":1,"metrics":["MAE mean (º)","MAE yaw (º)","MAE pitch (º)","MAE roll (º)"],"first_row_in_archive_order":{"model":"SPIGA","paper":"/paper/shape-preserving-facial-landmarks-with-graph","metrics":{"MAE mean (º)":"2.39","MAE pitch (º)":"2.24","MAE roll (º)":"1.71","MAE yaw (º)":"3.23"},"code_links":[{"title":"andresprados/spiga","url":"https://github.com/andresprados/spiga"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/shape-preserving-facial-landmarks-with-graph","title":"Shape Preserving Facial Landmarks with Graph Attention Networks","date":"2022-10-13","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/luvli-face-alignment-estimating-landmarks","title":"LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood","date":"2020-04-06","rows_on_this_dataset":1,"code_links":1,"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."}