Analysing Affective Behavior in the second ABAW2 Competition
This competition provides a standardized benchmark for researchers in affective computing, but it is incremental as it builds on a previous competition.
The paper describes the second Affective Behavior Analysis in-the-wild (ABAW2) Competition, which tackles the problem of automatically analyzing affect through three challenges: valence-arousal estimation, basic expression classification, and action unit detection, using the Aff-Wild2 database as a benchmark.
The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the second -- following the first very successful ABAW Competition held in conjunction with IEEE FG 2020- Competition that aims at automatically analyzing affect. ABAW2 is split into three Challenges, each one addressing one of the three main behavior tasks of valence-arousal estimation, basic expression classification and action unit detection. All three Challenges are based on a common benchmark database, Aff-Wild2, which is a large scale in-the-wild database and the first one to be annotated for all these three tasks. In this paper, we describe this Competition, to be held in conjunction with ICCV 2021. We present the three Challenges, with the utilized Competition corpora. We outline the evaluation metrics and present the baseline system with its results. More information regarding the Competition is provided in the Competition site: https://ibug.doc.ic.ac.uk/resources/iccv-2021-2nd-abaw.