{"url":"/dataset/adaptiope","name":"Adaptiope","full_name":null,"description_markdown":"Adaptiope is a domain adaptation dataset with 123 classes in the three domains synthetic, product and real life. One of the main goals of Adaptiope is to offer a clean and well curated set of images for domain adaptation. This was necessary as many other common datasets in the area suffer from label noise and low quality images. Additionally, Adaptiope's class set was chosen in a way that minimizes the overlap with the class set of the commonly used ImageNet pretraining, therefore preventing information leakage in a domain adaptation setup.","description_withheld":null,"homepage":"https://gitlab.com/tringwald/adaptiope","introduced_date":"2021-01-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/adaptiope-a-modern-benchmark-for-unsupervised","title":"Adaptiope: A Modern Benchmark for Unsupervised Domain Adaptation","first_author":"Tobias Ringwald","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Domain Adaptation","url":"/task/domain-adaptation","datasets_with_task":"/datasets/task/domain-adaptation"},{"name":"Unsupervised Domain Adaptation","url":"/task/unsupervised-domain-adaptation","datasets_with_task":"/datasets/task/unsupervised-domain-adaptation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Adaptiope"],"data_loaders":[],"num_papers_in_archive":9,"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."}