{"url":"/dataset/awa-1","name":"AwA","full_name":"Animals with Attributes","description_markdown":"**Animals with Attributes** (**AwA**) was a dataset for benchmarking transfer-learning algorithms, in particular attribute base classification. It consisted of 30475 images of 50 animals classes with six pre-extracted feature representations for each image. The animals classes are aligned with Osherson's classical class/attribute matrix, thereby providing 85 numeric attribute values for each class. Using the shared attributes, it is possible to transfer information between different classes.\r\nThe Animals with Attributes dataset was suspended. Its images are not available anymore because of copyright restrictions. A drop-in replacement, Animals with Attributes 2, is available instead.\r\n\r\nSource: [Transductive Multi-view Zero-Shot Learning](https://arxiv.org/abs/1501.04560)\r\nImage Source: [https://cvml.ist.ac.at/AwA/](https://cvml.ist.ac.at/AwA/)","description_withheld":null,"homepage":"https://cvml.ist.ac.at/AwA/","introduced_date":"2009-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Learning to detect unseen object classes by between-class attribute transfer","first_author":null,"url":"https://doi.org/10.1109/CVPR.2009.5206594"},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Zero-Shot Learning","url":"/task/zero-shot-learning","datasets_with_task":"/datasets/task/zero-shot-learning"},{"name":"Few-Shot Image Classification","url":"/task/few-shot-image-classification","datasets_with_task":"/datasets/task/few-shot-image-classification"},{"name":"Generalized Few-Shot Learning","url":"/task/generalized-few-shot-learning","datasets_with_task":"/datasets/task/generalized-few-shot-learning"},{"name":"Generalized Zero-Shot Learning","url":"/task/generalized-zero-shot-learning","datasets_with_task":"/datasets/task/generalized-zero-shot-learning"},{"name":"Concept-based Classification","url":"/task/concept-based-classification","datasets_with_task":"/datasets/task/concept-based-classification"},{"name":"Long-tail learning with class descriptors","url":"/task/long-tail-learning-with-class-descriptors","datasets_with_task":"/datasets/task/long-tail-learning-with-class-descriptors"}],"languages":[],"variants":["AWA - 0-Shot","AWA1 - 0-Shot","AWA-LT","AwA2","AwA"],"data_loaders":[],"num_papers_in_archive":264,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/long-tail-learning-with-class-descriptors-on-2","task":"Long-tail learning with class descriptors","dataset_variant":"AWA-LT","rows":5,"metrics":["Per-Class Accuracy","Long-Tailed Accuracy"],"first_row_in_archive_order":{"model":"DRAGON + Bal'Loss","paper":"/paper/long-tail-learning-with-attributes","metrics":{"Long-Tailed Accuracy":"92.2","Per-Class Accuracy":"76.2"},"code_links":[{"title":"dvirsamuel/DRAGON","url":"https://github.com/dvirsamuel/DRAGON"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-awa-0-shot","task":"Few-Shot Image Classification","dataset_variant":"AWA - 0-Shot","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"Synthesised Classifier","paper":"/paper/synthesized-classifiers-for-zero-shot","metrics":{"Accuracy":"72.9%"},"code_links":[{"title":"JudyYe/zero-shot-gcn","url":"https://github.com/JudyYe/zero-shot-gcn"},{"title":"ruotianluo/zsl-gcn-pth","url":"https://github.com/ruotianluo/zsl-gcn-pth"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-awa1-0-shot","task":"Few-Shot Image Classification","dataset_variant":"AWA1 - 0-Shot","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"TAFE-Net","paper":"/paper/tafe-net-task-aware-feature-embeddings-for-1","metrics":{"Accuracy":"70.8"},"code_links":[{"title":"ucbdrive/tafe-net","url":"https://github.com/ucbdrive/tafe-net"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/long-tail-learning-with-attributes","title":"From Generalized zero-shot learning to long-tail with class descriptors","date":"2020-04-05","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/decoupling-representation-and-classifier-for","title":"Decoupling Representation and Classifier for Long-Tailed Recognition","date":"2019-10-21","rows_on_this_dataset":1,"code_links":4,"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/learning-imbalanced-datasets-with-label","title":"Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss","date":"2019-06-18","rows_on_this_dataset":1,"code_links":7,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":2,"samples_unverified":9,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/generalized-zero-and-few-shot-learning-via-1","title":"Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders","date":"2019-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/tafe-net-task-aware-feature-embeddings-for-1","title":"TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning","date":"2019-04-11","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":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/synthesized-classifiers-for-zero-shot","title":"Synthesized Classifiers for Zero-Shot Learning","date":"2016-03-02","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":2,"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":4,"samples_harvested":19,"samples_ran":5,"samples_unverified":14,"pointer_only_for_licence":7,"papers_with_no_sample_that_ran":1,"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."}