{"url":"/dataset/egoshots","name":"EgoShots","full_name":null,"description_markdown":"Egoshots is a 2-month Ego-vision Dataset with Autographer Wearable Camera annotated \"for free\" with transfer learning. Three state of the art pre-trained image captioning models are used. The dataset represents the life of 2 interns while working at Philips Research (Netherlands) (May-July 2015) generously donating their data.\n\nSource: [https://github.com/NataliaDiaz/Egoshots](https://github.com/NataliaDiaz/Egoshots)","description_withheld":null,"homepage":"https://github.com/NataliaDiaz/Egoshots","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/egoshots-an-ego-vision-life-logging-dataset","title":"Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning models","first_author":"Pranav Agarwal","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Captioning","url":"/task/image-captioning","datasets_with_task":"/datasets/task/image-captioning"},{"name":"Object Recognition","url":"/task/object-recognition","datasets_with_task":"/datasets/task/object-recognition"}],"languages":[],"variants":["EgoShots"],"data_loaders":[{"repo":"https://github.com/NataliaDiaz/Egoshots","url":"https://github.com/NataliaDiaz/Egoshots","frameworks":[]}],"num_papers_in_archive":2,"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."}