{"url":"/dataset/sun-attribute","name":"SUN Attribute","full_name":"SUN Attribute","description_markdown":"The **SUN Attribute** dataset consists of 14,340 images from 717 scene categories, and each category is annotated with a taxonomy of 102 discriminate attributes. The dataset can be used for high-level scene understanding and fine-grained scene recognition.\r\n\r\nSource: [Zero-Shot Learning with Multi-Battery Factor Analysis](https://arxiv.org/abs/1606.09349)\r\nImage Source: [https://cs.brown.edu/~gmpatter/sunattributes.html](https://cs.brown.edu/~gmpatter/sunattributes.html)","description_withheld":null,"homepage":"https://cs.brown.edu/~gmpatter/sunattributes.html","introduced_date":"2014-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding","first_author":null,"url":"https://doi.org/10.1007/s11263-013-0695-z"},"license":{"name":"Custom (research-only, non-commercial)","url":"https://groups.csail.mit.edu/vision/datasets/ADE20K/terms/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Zero-Shot Learning","url":"/task/zero-shot-learning","datasets_with_task":"/datasets/task/zero-shot-learning"},{"name":"Object Recognition","url":"/task/object-recognition","datasets_with_task":"/datasets/task/object-recognition"},{"name":"Generalized Zero-Shot Learning","url":"/task/generalized-zero-shot-learning","datasets_with_task":"/datasets/task/generalized-zero-shot-learning"}],"languages":[],"variants":["SUN Attribute"],"data_loaders":[],"num_papers_in_archive":38,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/generalized-zero-shot-learning-on-sun","task":"Generalized Zero-Shot Learning","dataset_variant":"SUN Attribute","rows":9,"metrics":["Harmonic mean","H"],"first_row_in_archive_order":{"model":"ZeroDiff","paper":"/paper/exploring-data-efficiency-in-zero-shot","metrics":{"Harmonic mean":"59.8"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/zero-shot-learning-on-sun-attribute","task":"Zero-Shot Learning","dataset_variant":"SUN Attribute","rows":9,"metrics":["average top-1 classification accuracy","Accuracy Seen","Accuracy Unseen","H"],"first_row_in_archive_order":{"model":"ZeroDiff","paper":"/paper/exploring-data-efficiency-in-zero-shot","metrics":{"average top-1 classification accuracy":"77.3"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/exploring-data-efficiency-in-zero-shot","title":"Exploring Data Efficiency in Zero-Shot Learning with Diffusion Models","date":"2024-06-05","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/synthetic-sample-selection-for-generalized","title":"Synthetic Sample Selection for Generalized Zero-Shot Learning","date":"2023-04-06","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/duet-cross-modal-semantic-grounding-for","title":"DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning","date":"2022-07-04","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/zero-shot-logit-adjustment","title":"Zero-Shot Logit Adjustment","date":"2022-04-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/latent-embedding-feedback-and-discriminative","title":"Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification","date":"2020-03-17","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/transferable-contrastive-network-for","title":"Transferable Contrastive Network for Generalized Zero-Shot Learning","date":"2019-08-16","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/leveraging-the-invariant-side-of-generative","title":"Leveraging the Invariant Side of Generative Zero-Shot Learning","date":"2019-04-08","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/f-vaegan-d2-a-feature-generating-framework","title":"f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning","date":"2019-03-25","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/multi-modal-cycle-consistent-generalized-zero","title":"Multi-modal Cycle-consistent Generalized Zero-Shot Learning","date":"2018-08-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/feature-generating-networks-for-zero-shot","title":"Feature Generating Networks for Zero-Shot Learning","date":"2017-12-04","rows_on_this_dataset":2,"code_links":4,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":5,"samples_ran":2,"samples_unverified":3,"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."}