{"url":"/dataset/watercolor2k","name":"Watercolor2k","full_name":null,"description_markdown":"Watercolor2k is a dataset used for cross-domain object detection which contains 2k watercolor images with image and instance-level annotations.","description_withheld":null,"homepage":"https://naoto0804.github.io/cross_domain_detection/","introduced_date":"2018-03-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/cross-domain-weakly-supervised-object","title":"Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation","first_author":"Naoto Inoue","url":null},"license":null,"modalities":[],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Weakly Supervised Object Detection","url":"/task/weakly-supervised-object-detection","datasets_with_task":"/datasets/task/weakly-supervised-object-detection"},{"name":"Unsupervised Object Detection","url":"/task/unsupervised-object-detection","datasets_with_task":"/datasets/task/unsupervised-object-detection"},{"name":"Body Detection","url":"/task/body-detection","datasets_with_task":"/datasets/task/body-detection"}],"languages":[],"variants":["Watercolor2k"],"data_loaders":[],"num_papers_in_archive":37,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/weakly-supervised-object-detection-on-1","task":"Weakly Supervised Object Detection","dataset_variant":"Watercolor2k","rows":12,"metrics":["MAP"],"first_row_in_archive_order":{"model":"TADP","paper":"/paper/text-image-alignment-for-diffusion-based","metrics":{"MAP":"72.2"},"code_links":[{"title":"damaggu/tadp","url":"https://github.com/damaggu/tadp"},{"title":"nkondapa/RSVC","url":"https://github.com/nkondapa/RSVC"}]},"note":"rows are the archive's own order at snapshot; 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nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/text-image-alignment-for-diffusion-based","title":"Text-image Alignment for Diffusion-based Perception","date":"2023-09-29","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/semi-supervised-domain-generalization-for-1","title":"Semi-Supervised Domain Generalization for Object Detection via Language-Guided Feature Alignment","date":"2023-09-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/domain-adaptive-self-supervised-pre-training","title":"Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings","date":"2022-11-19","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/h2fa-r-cnn-holistic-and-hierarchical-feature","title":"H2FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection","date":"2022-01-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/informative-and-consistent-correspondence","title":"Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection","date":"2021-06-19","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/domain-adaptive-object-detection-via-1","title":"Domain-Adaptive Object Detection via Uncertainty-Aware Distribution Alignment","date":"2020-10-31","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multiple-instance-learning-on-deep-features","title":"Multiple instance learning on deep features for weakly supervised object detection with extreme domain shifts","date":"2020-08-03","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/adaptive-object-detection-with-dual-multi","title":"Adaptive Object Detection with Dual Multi-Label Prediction","date":"2020-03-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/weakly-supervised-object-detection-in","title":"Weakly Supervised Object Detection in Artworks","date":"2018-10-05","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/cross-domain-weakly-supervised-object","title":"Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation","date":"2018-03-30","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":11,"samples_ran":2,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/weakly-supervised-deep-detection-networks","title":"Weakly Supervised Deep Detection Networks","date":"2015-11-09","rows_on_this_dataset":1,"code_links":5,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":3,"samples_ran":1,"samples_unverified":2,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":2,"samples_harvested":14,"samples_ran":3,"samples_unverified":11,"pointer_only_for_licence":1,"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."}