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Intention-Conditioned Long-Term Human Egocentric Action Anticipation

Mascaro, Esteve Valls and Ahn, Hyemin and Lee, Dongheui (2023) Intention-Conditioned Long-Term Human Egocentric Action Anticipation. In: 23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023, pp. 6037-6046. IEEE. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision, 02-07 Jan 2023, Waikoloa, HI, USA. doi: 10.1109/WACV56688.2023.00599. ISBN 978-166549346-8. ISSN 2472-6737.

Full text not available from this repository.

Official URL: https://ieeexplore.ieee.org/document/10030492

Abstract

To anticipate how a person would act in the future, it is essential to understand the human intention since it guides the subject towards a certain action. In this paper, we propose a hierarchical architecture which assumes a sequence of human action (low-level) can be driven from the human intention (high-level). Based on this, we deal with long-term action anticipation task in egocentric videos. Our framework first extracts this low- and high-level human information over the observed human actions in a video through a Hierarchical Multi-task Multi-Layer Perceptrons Mixer (H3M). Then, we constrain the uncertainty of the future through an Intention-Conditioned Variational Auto-Encoder (I-CVAE) that generates multiple stable predictions of the next actions that the observed human might perform. By leveraging human intention as high-level information, we claim that our model is able to anticipate more time-consistent actions in the long-term, thus improving the results over the baseline in Ego4D dataset. This work results in the state-of-the-art for Long-Term Anticipation (LTA) task in Ego4D by providing more plausible anticipated sequences, improving the anticipation scores of nouns and actions. Our work ranked first in both CVPR@2022 and ECCV@2022 Ego4D LTA Challenge.

Item URL in elib:https://elib.dlr.de/197483/
Document Type:Conference or Workshop Item (Speech)
Title:Intention-Conditioned Long-Term Human Egocentric Action Anticipation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Mascaro, Esteve VallsTU WienUNSPECIFIEDUNSPECIFIED
Ahn, HyeminUNSPECIFIEDhttps://orcid.org/0000-0001-8081-6023UNSPECIFIED
Lee, DongheuiUNSPECIFIEDhttps://orcid.org/0000-0003-1897-7664UNSPECIFIED
Date:6 February 2023
Journal or Publication Title:23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.1109/WACV56688.2023.00599
Page Range:pp. 6037-6046
Publisher:IEEE
ISSN:2472-6737
ISBN:978-166549346-8
Status:Published
Keywords:Action Anticipation
Event Title:2023 IEEE/CVF Winter Conference on Applications of Computer Vision
Event Location:Waikoloa, HI, USA
Event Type:international Conference
Event Dates:02-07 Jan 2023
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Basic Technologies [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Strobl, Dr. Klaus H.
Deposited On:22 Sep 2023 12:56
Last Modified:22 Sep 2023 13:43

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