{"url":"/dataset/comic2k","name":"Comic2k","full_name":null,"description_markdown":"**Comic2k** is a dataset used for cross-domain object detection which contains 2k comic images with image and instance-level annotations.\r\nImage Source: [https://naoto0804.github.io/cross_domain_detection/](https://naoto0804.github.io/cross_domain_detection/)","description_withheld":null,"homepage":"https://naoto0804.github.io/cross_domain_detection/","introduced_date":"2018-01-01","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":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Domain Adaptation","url":"/task/domain-adaptation","datasets_with_task":"/datasets/task/domain-adaptation"},{"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"},{"name":"Object Proposal Generation","url":"/task/object-proposal-generation","datasets_with_task":"/datasets/task/object-proposal-generation"},{"name":"Class-agnostic Object Detection","url":"/task/class-agnostic-object-detection","datasets_with_task":"/datasets/task/class-agnostic-object-detection"}],"languages":[],"variants":["Comic2k"],"data_loaders":[],"num_papers_in_archive":29,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/weakly-supervised-object-detection-on-comic2k","task":"Weakly Supervised Object Detection","dataset_variant":"Comic2k","rows":8,"metrics":["MAP"],"first_row_in_archive_order":{"model":"DASS-Detector (YOLOX Tiny)","paper":"/paper/domain-adaptive-self-supervised-pre-training","metrics":{"MAP":"67.41"},"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/domain-adaptation-on-comic2k","task":"Domain Adaptation","dataset_variant":"Comic2k","rows":2,"metrics":[" mAP"],"first_row_in_archive_order":{"model":"DDT","paper":"/paper/diffusion-domain-teacher-diffusion-guided","metrics":{" mAP":"50.2"},"code_links":[{"title":"heboyong/Diffusion-Domain-Teacher","url":"https://github.com/heboyong/Diffusion-Domain-Teacher"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/body-detection-on-comic2k","task":"Body Detection","dataset_variant":"Comic2k","rows":1,"metrics":["MAP "],"first_row_in_archive_order":{"model":"DASS-Detector (YOLOX XL)","paper":"/paper/domain-adaptive-self-supervised-pre-training","metrics":{"MAP ":"73.65"},"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-comic2k","task":"Object Detection","dataset_variant":"Comic2k","rows":1,"metrics":["mAP"],"first_row_in_archive_order":{"model":"CDDMSL","paper":"/paper/semi-supervised-domain-generalization-for-1","metrics":{"mAP":"45.9"},"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/diffusion-domain-teacher-diffusion-guided","title":"Diffusion Domain Teacher: Diffusion Guided Domain Adaptive Object Detector","date":"2025-06-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"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/mila-memory-based-instance-level-adaptation-1","title":"MILA: Memory-Based Instance-Level Adaptation for Cross-Domain Object Detection","date":"2023-09-03","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/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":2,"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."}