2023-12-02-mascaro23a.md

title	section	openreview	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
HOI4ABOT: Human-Object Interaction Anticipation for Human Intention Reading Collaborative roBOTs	Poster	rYZBdBytxBx	Robots are becoming increasingly integrated into our lives, assisting us in various tasks. To ensure effective collaboration between humans and robots, it is essential that they understand our intentions and anticipate our actions. In this paper, we propose a Human-Object Interaction (HOI) anticipation framework for collaborative robots. We propose an efficient and robust transformer-based model to detect and anticipate HOIs from videos. This enhanced anticipation empowers robots to proactively assist humans, resulting in more efficient and intuitive collaborations. Our model outperforms state-of-the-art results in HOI detection and anticipation in VidHOI dataset with an increase of $1.76%$ and $1.04%$ in mAP respectively while being 15.4 times faster. We showcase the effectiveness of our approach through experimental results in a real robot, demonstrating that the robot’s ability to anticipate HOIs is key for better Human-Robot Interaction.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	mascaro23a	0	HOI4ABOT: Human-Object Interaction Anticipation for Human Intention Reading Collaborative roBOTs	1111	1130	1111-1130	1111	false	Mascaro, Esteve Valls and Sliwowski, Daniel and Lee, Dongheui	given family Esteve Valls Mascaro given family Daniel Sliwowski given family Dongheui Lee	2023-12-02		Proceedings of The 7th Conference on Robot Learning	229	inproceedings	date-parts 2023 12 2	https://proceedings.mlr.press/v229/mascaro23a/mascaro23a.pdf