Abstract

This talk aims to argue for a fine-grained perspective onto human-object interactions, from video sequences. I will present approaches for determining skill or expertise from video sequences [CVPR 2019, CVPR 2018], assessing action ‘completion’ – i.e. when an interaction is attempted but not completed [BMVC 2018], dual-domain and dual-time learning [CVPR 2019, ICCVW 2019] as well as multi-modal approaches using vision, audio and language [ICCV 2019, BMVC 2019].I will also introduce Epic-Kitchens [ECCV 2018], the recently released largest dataset of object interactions in people’s homes, recorded using wearable cameras. The dataset includes 11.5M frames fully annotated with objects and actions, based on unique annotations from the participants narrating their own videos, thus reflecting true intention. Three open challenges are now available on object detection, action recognition and action anticipation at Epic-Kitchens http://epic-kitchens.github.io

Bio |  Received her PhD from the University of Leeds (2009). Dima’s research interests are in the automatic understanding of object interactions, actions and activities using static and wearable visual (and depth) sensors. Dima co-chaired BMVC 2013, is area chair for BMVC (2014-2019), associate editor of Pattern Recognition (2017-) and IET Computer Vision (2013-). She was selected as a Nokia Research collaborator in 2016, and as an Outstanding Reviewer in ICCV17, CVPR13 and CVPR12.  More details at: http://dimadamen.github.io