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

• Main Authors: Damen, Dima, Doughty, Hazel, Farinella, Giovanni Maria, Furnari, Antonino, Kazakos, Evangelos, Ma, Jian, Moltisanti, Davide, Munro, Jonathan, Perrett, Toby, Price, Will, Wray, Michael
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Video Dataset; Annotation Quality
• Online Access: https://hdl.handle.net/10356/162036
• Institution: Nanyang Technological University

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...