{"url":"/dataset/tao-amodal","name":"TAO-Amodal","full_name":null,"description_markdown":"Our dataset augments the TAO dataset with amodal bounding box annotations for fully invisible, out-of-frame, and occluded objects. Note that this implies TAO-Amodal also includes modal segmentation masks (as visualized in the color overlays above). Our dataset encompasses 880 categories, aimed at assessing the occlusion reasoning capabilities of current trackers through the paradigm of Tracking Any Object with Amodal perception (TAO-Amodal).","description_withheld":null,"homepage":"https://huggingface.co/datasets/chengyenhsieh/TAO-Amodal","introduced_date":"2023-12-19","introduced_date_note":null,"introduced_by":{"paper":"/paper/tracking-any-object-amodally","title":"TAO-Amodal: A Benchmark for Tracking Any Object Amodally","first_author":"Cheng-Yen Hsieh","url":null},"license":{"name":"MIT","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Multi-Object Tracking","url":"/task/multi-object-tracking","datasets_with_task":"/datasets/task/multi-object-tracking"},{"name":"Amodal Tracking","url":"/task/amodal-tracking","datasets_with_task":"/datasets/task/amodal-tracking"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["TAO-Amodal"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}