3 citations · 4 across the 5 of their papers we have counts for
5 papers
SigmaCollab: An Application-Driven Dataset for Physically Situated Collaboration
Dan Bohus, Sean Andrist, Ann Paradiso +3
We introduce SigmaCollab, a dataset enabling research on physically situated human-AI collaboration. The dataset consists of a set of 85 sessions in which untrained participants we…
Learning to Recognize Correctly Completed Procedure Steps in Egocentric Assembly Videos through Spatio-Temporal Modeling
Tim J. Schoonbeek, Shao-Hsuan Hung, Dan Lehman +4
Procedure step recognition (PSR) aims to identify all correctly completed steps and their sequential order in videos of procedural tasks. The existing state-of-the-art models rely…
Find the Assembly Mistakes: Error Segmentation for Industrial Applications
Dan Lehman, Tim J. Schoonbeek, Shao-Hsuan Hung +3
Recognizing errors in assembly and maintenance procedures is valuable for industrial applications, since it can increase worker efficiency and prevent unplanned down-time. Although…
Supervised Representation Learning towards Generalizable Assembly State Recognition
Tim J. Schoonbeek, Goutham Balachandran, Hans Onvlee +5
Assembly state recognition facilitates the execution of assembly procedures, offering feedback to enhance efficiency and minimize errors. However, recognizing assembly states poses…
IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like Setting
Tim J. Schoonbeek, Tim Houben, Hans Onvlee +2
Although action recognition for procedural tasks has received notable attention, it has a fundamental flaw in that no measure of success for actions is provided. This limits the ap…