{"url":"/dataset/nao","name":"NAO","full_name":"Natural Adversarial Object","description_markdown":"**Natural Adversarial Objects** (**NAO**) is a new dataset to evaluate the robustness of object detection models. NAO contains 7,934 images and 9,943 objects that are unmodified and representative of real-world scenarios, but cause state-of-the-art detection models to misclassify with high confidence.","description_withheld":null,"homepage":"https://drive.google.com/drive/folders/15P8sOWoJku6SSEiHLEts86ORfytGezi8?usp=sharing","introduced_date":"2021-11-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/natural-adversarial-objects","title":"Natural Adversarial Objects","first_author":"Felix Lau","url":null},"license":{"name":"None","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"}],"languages":[],"variants":["NAO"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-on-nao","task":"Object Detection","dataset_variant":"NAO","rows":7,"metrics":["mAP","mAP w/o OOD","mAR"],"first_row_in_archive_order":{"model":"Mask RCNN R50","paper":"/paper/natural-adversarial-objects","metrics":{"mAP":"15.2","mAP w/o OOD":"24.6","mAR":"43.8"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/natural-adversarial-objects","title":"Natural Adversarial Objects","date":"2021-11-07","rows_on_this_dataset":7,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"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."}