{"url":"/dataset/labelme","name":"LabelMe","full_name":null,"description_markdown":"**LabelMe** database is a large collection of images with ground truth labels for object detection and recognition. The annotations come from two different sources, including the LabelMe online annotation tool.\r\n\r\nSource: [LabelMe: A Database and Web-Based Tool for Image Annotation](https://people.csail.mit.edu/brussell/research/AIM-2005-025-new.pdf)\r\nImage Source: [Russell et al](https://people.csail.mit.edu/brussell/research/AIM-2005-025-new.pdf)","description_withheld":null,"homepage":"http://labelme.csail.mit.edu/Release3.0/index.php","introduced_date":"2008-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"LabelMe: A Database and Web-Based Tool for Image Annotation","first_author":null,"url":"https://people.csail.mit.edu/brussell/research/AIM-2005-025-new.pdf"},"license":{"name":"Public domain","url":"http://labelme.csail.mit.edu/Release3.0/browserTools/php/LabelMeHelp.php#:~:text=Licenses"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["LabelMe"],"data_loaders":[],"num_papers_in_archive":178,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-classification-on-labelme","task":"Image Classification","dataset_variant":"LabelMe","rows":1,"metrics":["Test Accuracy"],"first_row_in_archive_order":{"model":"CoNAL","paper":"/paper/learning-from-crowds-by-modeling-common","metrics":{"Test Accuracy":"87.12"},"code_links":[{"title":"seunghyukcho/CoNAL-pytorch","url":"https://github.com/seunghyukcho/CoNAL-pytorch"},{"title":"seunghyukcho/doctornet-pytorch","url":"https://github.com/seunghyukcho/doctornet-pytorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/learning-from-crowds-by-modeling-common","title":"Learning from Crowds by Modeling Common Confusions","date":"2020-12-24","rows_on_this_dataset":1,"code_links":2,"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."}