54 citations · 76 across the 8 of their papers we have counts for
5 papers · 1 filter
FEEL (Force-Enhanced Egocentric Learning): A Dataset for Physical Action Understanding
Eadom Dessalene, Botao He, Michael Maynord +5
We introduce FEEL (Force-Enhanced Egocentric Learning), the first large-scale dataset pairing force measurements gathered from custom piezoresistive gloves with egocentric video. O…
LEAP: LLM-Generation of Egocentric Action Programs
Eadom Dessalene, Michael Maynord, Cornelia Fermüller +1
We introduce LEAP (illustrated in Figure 1), a novel method for generating video-grounded action programs through use of a Large Language Model (LLM). These action programs represe…
Therbligs in Action: Video Understanding through Motion Primitives
Eadom Dessalene, Michael Maynord, Cornelia Fermuller +1
In this paper we introduce a rule-based, compositional, and hierarchical modeling of action using Therbligs as our atoms. Introducing these atoms provides us with a consistent, exp…
Forecasting Action through Contact Representations from First Person Video
Eadom Dessalene, Chinmaya Devaraj, Michael Maynord +2
Human actions involving hand manipulations are structured according to the making and breaking of hand-object contact, and human visual understanding of action is reliant on antici…
Egocentric Object Manipulation Graphs
Eadom Dessalene, Michael Maynord, Chinmaya Devaraj +2
We introduce Egocentric Object Manipulation Graphs (Ego-OMG) - a novel representation for activity modeling and anticipation of near future actions integrating three components: 1)…