{"url":"/dataset/horse-10","name":"Horse-10","full_name":null,"description_markdown":"**Horse-10** is an animal pose estimation dataset. It comprises 30 diverse Thoroughbred horses, for which 22 body parts were labeled by an expert in *8,114* frames (animal pose estimation). Horses have various coat colors and the “in-the-wild” aspect of the collected data at various Thoroughbred yearling sales and farms added additional complexity.  The authors introduce Horse-C to contrast the domain shift inherent in the Horse-10 dataset with domain shift induced by common image corruptions.","description_withheld":null,"homepage":"http://horse10.deeplabcut.org","introduced_date":"2019-09-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/pretraining-boosts-out-of-domain-robustness","title":"Pretraining boosts out-of-domain robustness for pose estimation","first_author":"Alexander Mathis","url":null},"license":{"name":"non-commercial use only, with attribution","url":"http://horse10.deeplabcut.org"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Animal Pose Estimation","url":"/task/animal-pose-estimation","datasets_with_task":"/datasets/task/animal-pose-estimation"}],"languages":[],"variants":["Horse-10"],"data_loaders":[{"repo":"https://github.com/open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose/blob/master/docs/tasks/2d_animal_keypoint.md#horse-10","frameworks":["pytorch"]},{"repo":"https://github.com/DeepLabCut/DeepLabCut","url":"https://deeplabcut.github.io/DeepLabCut/README.html","frameworks":["tf"]}],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/animal-pose-estimation-on-horse-10","task":"Animal Pose Estimation","dataset_variant":"Horse-10","rows":8,"metrics":["PCK@0.3 (OOD)","Normalized Error (OOD)"],"first_row_in_archive_order":{"model":"DeepLabCut-EfficientNet-B6","paper":"/paper/pretraining-boosts-out-of-domain-robustness","metrics":{"PCK@0.3 (OOD)":"88.4"},"code_links":[{"title":"DeepLabCut/DeepLabCut","url":"https://github.com/DeepLabCut/DeepLabCut"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/panoptic-animal-pose-estimators-are-zero-shot","title":"SuperAnimal pretrained pose estimation models for behavioral analysis","date":"2022-03-14","rows_on_this_dataset":2,"code_links":3,"syntology":null},{"paper":"/paper/pretraining-boosts-out-of-domain-robustness","title":"Pretraining boosts out-of-domain robustness for pose estimation","date":"2019-09-24","rows_on_this_dataset":6,"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."}