{"url":"/dataset/clipart1k","name":"Clipart1k","full_name":null,"description_markdown":"In Clipart1k, the target domain classes to be detected are the same as those in the source domain. All the images for a clipart domain were collected from one dataset (i.e., CMPlaces) and two image search engines (i.e., Openclipart2 and Pixabay3). Search queries used are 205 scene classes (e.g., pasture) used in CMPlaces to collect various objects and scenes with complex backgrounds.","description_withheld":null,"homepage":"https://github.com/naoto0804/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":[],"data_loaders":[],"num_papers_in_archive":48,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/weakly-supervised-object-detection-on-2","task":"Weakly Supervised Object Detection","dataset_variant":"Clipart1k","rows":7,"metrics":["MAP"],"first_row_in_archive_order":{"model":"H2FA R-CNN (clipart_all)","paper":"/paper/h2fa-r-cnn-holistic-and-hierarchical-feature","metrics":{"MAP":"69.8"},"code_links":[{"title":"xuyunqiu/h2fa_r-cnn","url":"https://github.com/xuyunqiu/h2fa_r-cnn"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/body-detection-on-clipart1k","task":"Body Detection","dataset_variant":"Clipart1k","rows":1,"metrics":["MAP "],"first_row_in_archive_order":{"model":"DASS-Detector (YOLOX XL)","paper":"/paper/domain-adaptive-self-supervised-pre-training","metrics":{"MAP ":"83.59"},"code_links":[{"title":"barisbatuhan/dass_det_inference","url":"https://github.com/barisbatuhan/dass_det_inference"},{"title":"barisbatuhan/dass_detector","url":"https://github.com/barisbatuhan/dass_detector"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-detection-on-clipart1k","task":"Object Detection","dataset_variant":"Clipart1k","rows":1,"metrics":["MAP"],"first_row_in_archive_order":{"model":"CDDMSL","paper":"/paper/semi-supervised-domain-generalization-for-1","metrics":{"MAP":"39.8"},"code_links":[{"title":"sinamalakouti/CDDMSL","url":"https://github.com/sinamalakouti/CDDMSL"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"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/cross-domain-weakly-supervised-object","title":"Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation","date":"2018-03-30","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":1,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":11,"samples_ran":1,"samples_unverified":10,"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."}