{"url":"/dataset/imageclef-da","name":"ImageCLEF-DA","full_name":"ImageCLEF-DA","description_markdown":"The **ImageCLEF-DA** dataset is a benchmark dataset for ImageCLEF 2014 domain adaptation challenge, which contains three domains: Caltech-256 (C), ImageNet ILSVRC 2012 (I) and Pascal VOC 2012 (P). For each domain, there are 12 categories and 50 images in each category.\r\n\r\nSource: [Domain-Symmetric Networks for Adversarial Domain Adaptation](https://arxiv.org/abs/1904.04663)\r\nImage Source: [https://www.imageclef.org/2014/adaptation](https://www.imageclef.org/2014/adaptation)","description_withheld":null,"homepage":"https://www.imageclef.org/2014/adaptation","introduced_date":"2017-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/deep-transfer-learning-with-joint-adaptation","title":"Deep Transfer Learning with Joint Adaptation Networks","first_author":"Mingsheng Long","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Domain Adaptation","url":"/task/domain-adaptation","datasets_with_task":"/datasets/task/domain-adaptation"},{"name":"Multi-Source Unsupervised Domain Adaptation","url":"/task/multi-source-unsupervised-domain-adaptation","datasets_with_task":"/datasets/task/multi-source-unsupervised-domain-adaptation"},{"name":"Scene Graph Detection","url":"/task/scene-graph-detection","datasets_with_task":"/datasets/task/scene-graph-detection"},{"name":"Predicate Classification","url":"/task/predicate-classification","datasets_with_task":"/datasets/task/predicate-classification"},{"name":"Scene Graph Classification","url":"/task/scene-graph-classification","datasets_with_task":"/datasets/task/scene-graph-classification"}],"languages":[],"variants":["ImageCLEF-DA"],"data_loaders":[],"num_papers_in_archive":96,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/domain-adaptation-on-imageclef-da","task":"Domain Adaptation","dataset_variant":"ImageCLEF-DA","rows":17,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"CMKD","paper":"/paper/unsupervised-domain-adaption-harnessing","metrics":{"Accuracy":"94.3"},"code_links":[{"title":"Wenlve-Zhou/VLP-UDA","url":"https://github.com/Wenlve-Zhou/VLP-UDA"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/unsupervised-domain-adaption-harnessing","title":"Unsupervised Domain Adaption Harnessing Vision-Language Pre-training","date":"2024-04-19","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/reusing-the-task-specific-classifier-as-a","title":"Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation","date":"2022-04-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/global-local-regularization-via","title":"Global-Local Regularization Via Distributional Robustness","date":"2022-03-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bridging-adversarial-and-statistical-domain","title":"Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks","date":"2021-02-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/discriminative-feature-alignment","title":"Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment","date":"2020-06-23","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/entropy-minimization-vs-diversity","title":"Entropy Minimization vs. Diversity Maximization for Domain Adaptation","date":"2020-02-05","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":1,"samples_unverified":2,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dual-adversarial-domain-adaptation","title":"Dual Adversarial Domain Adaptation","date":"2020-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/correlation-aware-adversarial-domain","title":"Correlation-aware Adversarial Domain Adaptation and Generalization","date":"2019-11-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/unsupervised-domain-adaptation-via-structured","title":"Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling","date":"2019-11-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/transfer-learning-with-dynamic-distribution","title":"Transfer Learning with Dynamic Distribution Adaptation","date":"2019-09-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/attending-to-discriminative-certainty-for-1","title":"Attending to Discriminative Certainty for Domain Adaptation","date":"2019-06-08","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/looking-back-at-labels-a-class-based-domain","title":"Looking back at Labels: A Class based Domain Adaptation Technique","date":"2019-04-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/easy-transfer-learning-by-exploiting-intra","title":"Easy Transfer Learning By Exploiting Intra-domain Structures","date":"2019-04-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/cluster-alignment-with-a-teacher-for","title":"Cluster Alignment with a Teacher for Unsupervised Domain Adaptation","date":"2019-03-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/unsupervised-domain-adaptation-an-adaptive","title":"Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation","date":"2018-11-19","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/learning-transferable-features-with-deep","title":"Learning Transferable Features with Deep Adaptation Networks","date":"2015-02-10","rows_on_this_dataset":1,"code_links":5,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"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":5,"samples_harvested":9,"samples_ran":5,"samples_unverified":4,"pointer_only_for_licence":5,"papers_with_no_sample_that_ran":2,"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."}