[iva] Invitation to participate in: (1) the Affective Behavior Analysis in-the-wild 2020 Competition and/or (2) the related Workshop

[Kollias, Dimitrios]

Dear Colleagues,

Please find below the invitation to contribute to:

(1) the Affective Behavior Analysis in-the-wild Competition-Challenge
and/or
(2) the Affect Recognition in-the-wild: Uni/Multi-Modal Analysis Workshop,

to be held in conjunction with the IEEE Automatic Face and Gesture Recognition (FG) Conference 2020 in Buenos Aires, Argentina, 18-22 May 2020.

(1): The Competition is split into three Challenges-Tracks, which are based, for the first time, on the same database, Aff-Wild2, which is the first comprehensive benchmark for the three affect recognition tasks in-the-wild:
i)  dimensional affect recognition (valence and arousal estimation),
ii) categorical affect classification (seven basic expression classification)
and
iii) facial action unit detection
Aff-Wild2 is an audiovisual database of 564 videos of around 2.8M frames.

Participants are invited to participate in one or more of these Challenges.
There will be one winner per Challenge-Track; the winners are expected to contribute a paper describing their approach, methodology and results; the accepted winning papers will be part of the IEEE FG 2020 proceedings; all other teams will be able to able to submit a paper describing their solutions and final results to the Workshop that we are also organizing entitled 'Affect Recognition in-the-wild: Uni/Multi-Modal Analysis'.

For the purpose of the Challenges and to facilitate training, especially for people that do not have access to face detectors/tracking algorithms, we provide the cropped images and the cropped & aligned ones.

For more information about the challenge, see https://ibug.doc.ic.ac.uk/resources/fg-2020-competition-affective-behavior-analysis/

To participate, you need to register your team. For this, please send us an email to:
dimitrios.kollias15 at imperial.ac.uk<mailto:dimitrios.kollias15 at imperial.ac.uk>
with the title "Affective Behavior Analysis in-the-wild Competition: Team Registration". In this email include the following information:
Team Name
Team Members
Affiliation

There is no maximum number of participants in each team.
As a reply, you will receive the access to the dataset's videos, annotations, cropped/cropped-aligned images and other important information.

At the end of the Challenges, each team will have to send us: i) their predictions on the test set, ii) a link to a Github repository where their solution/source code will be stored, and iii) a link to an ArXiv paper with 2-6 pages describing their proposed methodology, data used and results. After that, the winner of each Challenge will be announced and all (non-winning) teams will be able to submit a paper describing their solutions and final results to the Workshop that we are also organizing entitled 'Affect Recognition in-the-wild: Uni/Multi-Modal Analysis'.


Submission deadlines are as follows:

•   18 November 2019 - Call for participation announced, team registration begins, data available

•   4 February 2020 - Final submission deadline (Results, Code and ArXiv paper)

•   5 February 2020 - Winners Announcement

•   14 February 2020 - Final paper submission deadline

•   21 February 2020 -  Review decisions sent to authors; Notification of acceptance

•   28 February 2020 - Camera ready version deadline


Chairs:


Stefanos Zafeiriou, Imperial College London, UK

Dimitrios Kollias, Imperial College London, UK

Attila Schulc,  Realeyes - Emotional Intelligence

Elnar Hajiyev, Realeyes- Emotional Intelligence



(2): The workshop aims at advancing the state-of-the-art in the problem of analysis of human affective behavior in-the-wild. At first, non-winning papers describing their solutions/methodologies to the three afore-mentioned Challenges will be invited for publication to the Workshop.
In addition, the Workshop does not only focus on the three Challenges. It will solicit any original paper on databases, benchmarks and technical contributions related to affect recognition, using audio, visual or other modalities (e.g., EEG), in unconstrained conditions. Either uni-modal, or multi-modal approaches will be considered. It would be of particular interest to see methodologies that study detection of action units based on audio data.

The scope of the workshop includes but is not limited to:

  *    the 3 Challenges on:
     i) Valence-Arousal estimation,
     ii) Action Unit detection and
     iii) 7 Basic Expression classification;
  *   contributions in the following topics:
   (a) databases for spontaneous and naturalistic:
           i) facial expression or micro-expression analysis, or
           ii) facial action unit detection, or
          iii) valence-arousal estimation, ”in the-wild”.
   (b) methodologies for:
           i) facial expression or micro-expression analysis, or
           ii) facial action unit detection, or
          iii) valence-arousal estimation, ”in the wild”;
 The methodologies can use uni-modal or multi-modal information (e.g., visual, audio data, hand and body gestures, EEG, EDA)
   (c) methodologies for action unit prediction from audio (e.g., using Aff-Wild2, which is an audiovisual database)
   (d) domain-adaptation techniques for the above described behavior tasks (either using Aff-Wild2, or any other database, or combination of databases).


IMPORTANT DATES:
-----------------------------

•   14 February 2020 - Paper submission deadline
•   21 February 2020 -  Review decisions sent to authors; Notification of acceptance
•   28 February 2020 - Camera ready version deadline

Accepted workshop papers will appear at IEEE FG 2020 proceedings.


Chairs:


Stefanos Zafeiriou, Imperial College London, UK

Dimitrios Kollias, Imperial College London, UK

Attila Schulc,  Realeyes - Emotional Intelligence



In case of any queries, please contact dimitrios.kollias15 at imperial.ac.uk<mailto:dimitrios.kollias15 at imperial.ac.uk> .




Kind Regards,

Dimitrios Kollias,
on behalf of the organising committee



iBUG Group
Department of Computing
Imperial College London




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