{"url":"/dataset/aria-everyday-objects","name":"Aria Everyday Objects","full_name":"Aria Everyday Objects","description_markdown":"A small-scale, real-world Project Aria dataset with high quality static 3D oriented bounding boxs annotations.\r\n\r\nDataset Contents\r\n- Project Aria glasses data (including 2 x SLAM cameras, 1 x RGB camera, 2 x IMU, and complete sensor calibrations)\r\n- Aria machine perception service annotations including semi-dense point clouds and 6DoF device trajectory.\r\n- Manually-annotated 3D object bounding boxes\r\n\r\nSequence Metrics\r\n- 45 minutes of egocentric recordings captured by non-computer vision experts across 25 diverse, primarily indoor, real-world environments\r\n- 1037 3D object bounding box instances across 17 classes: Bed, Chair, Couch, Door, Floor, Lamp, Mirror, Plant, Refrigerator, Screen, Sink, Storage, Table, Wall, WallArt, WasherDryer, and Window","description_withheld":null,"homepage":"https://www.projectaria.com/datasets/aeo/","introduced_date":"2024-09-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/efm3d-a-benchmark-for-measuring-progress","title":"EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models","first_author":"Julian Straub","url":null},"license":{"name":"Non-Commercial","url":"https://www.projectaria.com/datasets/aeo/license/"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"}],"tasks":[{"name":"3D Object Detection","url":"/task/3d-object-detection","datasets_with_task":"/datasets/task/3d-object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Aria Everyday Objects"],"data_loaders":[{"repo":"https://github.com/facebookresearch/efm3d","url":"https://github.com/facebookresearch/efm3d","frameworks":["pytorch"]},{"repo":"https://github.com/facebookresearch/ATEK","url":"https://github.com/facebookresearch/ATEK","frameworks":["pytorch"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-object-detection-on-aeo","task":"3D Object Detection","dataset_variant":"Aria Everyday Objects","rows":4,"metrics":["mAP"],"first_row_in_archive_order":{"model":"EVL","paper":"/paper/efm3d-a-benchmark-for-measuring-progress","metrics":{"mAP":"22"},"code_links":[{"title":"facebookresearch/efm3d","url":"https://github.com/facebookresearch/efm3d"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/efm3d-a-benchmark-for-measuring-progress","title":"EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models","date":"2024-06-14","rows_on_this_dataset":4,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"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":1,"samples_harvested":3,"samples_ran":3,"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."}