{"url":"/dataset/moet","name":"MOET","full_name":null,"description_markdown":"**MOET** a dataset consists of gaze data from participants tracking specific objects, annotated with labels and bounding boxes, in crowded real-world videos, for training and evaluating attention decoding algorithms.\r\n\r\nSource:[Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models](https://arxiv.org/pdf/2211.10966v1.pdf)\r\n\r\nImage Source: [https://arxiv.org/pdf/2211.10966v1.pdf](https://arxiv.org/pdf/2211.10966v1.pdf)","description_withheld":null,"homepage":"https://github.com/karan-uppal3/decoding-attention","introduced_date":"2022-11-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/decoding-attention-from-gaze-a-benchmark","title":"Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models","first_author":"Karan Uppal","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[],"languages":[],"variants":["MOET"],"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":"2026-09-25T09:33:49+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."}