Aff-Wild: Valence and Arousal ‘in-the-wild’ Challenge

Conference paper


Zafeiriou, S., Kollias, D., Nicolaou, M., Papaioannou, A., Zhao, G. and Kotsia, I. 2017. Aff-Wild: Valence and Arousal ‘in-the-wild’ Challenge. CVPRW 2017: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Honolulu, HI, USA 21 - 26 Jul 2017 Institute of Electrical and Electronics Engineers (IEEE). pp. 1980-1987 https://doi.org/10.1109/CVPRW.2017.248
TypeConference paper
TitleAff-Wild: Valence and Arousal ‘in-the-wild’ Challenge
AuthorsZafeiriou, S., Kollias, D., Nicolaou, M., Papaioannou, A., Zhao, G. and Kotsia, I.
Abstract

The Affect-in-the-Wild (Aff-Wild) Challenge proposes a new comprehensive benchmark for assessing the performance of facial affect/behaviour analysis/understanding 'in-the-wild'. The Aff-wild benchmark contains about 300 videos (over 2,000 minutes of data) annotated with regards to valence and arousal, all captured 'in-the-wild' (the main source being Youtube videos). The paper presents the database description, the experimental set up, the baseline method used for the Challenge and finally the summary of the performance of the different methods submitted to the Affect-in-the-Wild Challenge for Valence and Arousal estimation. The challenge demonstrates that meticulously designed deep neural networks can achieve very good performance when trained with in-the-wild data.

LanguageEnglish
ConferenceCVPRW 2017: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Page range1980-1987
ISSN2160-7516
ISBN
Electronic9781538607336
Paperback9781538607343
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publication dates
Print21 Jul 2017
Online24 Aug 2017
Publication process dates
Deposited16 Jun 2017
Accepted06 May 2017
Output statusPublished
Accepted author manuscript
Digital Object Identifier (DOI)https://doi.org/10.1109/CVPRW.2017.248
Book title2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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