Rescaling egocentric vision: collection, pipeline and challenges for EPIC-KITCHENS-100

Rescaling egocentric vision: collection, pipeline and challenges for EPIC-KITCHENS-100

This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head...

Полное описание

Библиографические подробности
Главные авторы:	Damen, Dima, Doughty, Hazel, Farinella, Giovanni Maria, Furnari, Antonino, Kazakos, Evangelos, Ma, Jian, Moltisanti, Davide, Munro, Jonathan, Perrett, Toby, Price, Will, Wray, Michael
Другие авторы:	School of Computer Science and Engineering
Формат:	Journal Article
Язык:	English
Опубликовано:	2022
Предметы:	Engineering::Computer science and engineering Video Dataset Annotation Quality
Online-ссылка:	https://hdl.handle.net/10356/162036

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