{"url":"/dataset/nabirds","name":"NABirds","full_name":"North America Birds","description_markdown":"**NABirds** V1 is a collection of 48,000 annotated photographs of the 400 species of birds that are commonly observed in North America. More than 100 photographs are available for each species, including separate annotations for males, females and juveniles that comprise 700 visual categories. This dataset is to be used for fine-grained visual categorization experiments.\r\n\r\nSource: [https://dl.allaboutbirds.org/nabirds](https://dl.allaboutbirds.org/nabirds)\r\nImage Source: [https://openaccess.thecvf.com/content_cvpr_2015/papers/Horn_Building_a_Bird_2015_CVPR_paper.pdf](https://openaccess.thecvf.com/content_cvpr_2015/papers/Horn_Building_a_Bird_2015_CVPR_paper.pdf)","description_withheld":null,"homepage":"https://dl.allaboutbirds.org/nabirds","introduced_date":"2015-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/building-a-bird-recognition-app-and-large","title":"Building a Bird Recognition App and Large Scale Dataset With Citizen Scientists: The Fine Print in Fine-Grained Dataset Collection","first_author":"Grant Van Horn","url":null},"license":{"name":"Custom","url":"https://dl.allaboutbirds.org/nabirds"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Fine-Grained Image Classification","url":"/task/fine-grained-image-classification","datasets_with_task":"/datasets/task/fine-grained-image-classification"}],"languages":[],"variants":["NABirds"],"data_loaders":[{"repo":"https://github.com/activeloopai/Hub","url":"https://docs.activeloop.ai/datasets/nabirds-dataset","frameworks":["tf","pytorch"]}],"num_papers_in_archive":143,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/fine-grained-image-classification-on-nabirds","task":"Fine-Grained Image Classification","dataset_variant":"NABirds","rows":30,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"MetaFormer\n(MetaFormer-2,384)","paper":"/paper/metaformer-a-unified-meta-framework-for-fine","metrics":{"Accuracy":"93.0%"},"code_links":[{"title":"dqshuai/metaformer","url":"https://github.com/dqshuai/metaformer"},{"title":"salluru007/papers","url":"https://github.com/salluru007/papers"}]},"note":"rows are the archive's own order at snapshot; 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not a correctness claim."}},{"paper":"/paper/context-aware-attentional-pooling-cap-for","title":"Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification","date":"2021-01-17","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/end-to-end-learning-of-a-fisher-vector","title":"End-to-end Learning of a Fisher Vector Encoding for Part Features in Fine-grained Recognition","date":"2020-07-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-attentive-pairwise-interaction-for","title":"Learning Attentive Pairwise Interaction for Fine-Grained Classification","date":"2020-02-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; 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not a correctness claim."}},{"paper":"/paper/maximum-entropy-fine-grained-classification","title":"Maximum-Entropy Fine Grained Classification","date":"2018-12-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/aligned-to-the-object-not-to-the-image-a","title":"Aligned to the Object, not to the Image: A Unified Pose-aligned Representation for Fine-grained Recognition","date":"2018-01-27","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/pairwise-confusion-for-fine-grained-visual","title":"Pairwise Confusion for Fine-Grained Visual Classification","date":"2017-05-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bilinear-cnns-for-fine-grained-visual","title":"Bilinear CNNs for Fine-grained Visual Recognition","date":"2015-04-29","rows_on_this_dataset":1,"code_links":4,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":5,"samples_harvested":23,"samples_ran":5,"samples_unverified":18,"pointer_only_for_licence":6,"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."}