  This paper describes the third Affective Behavior Analysis in-the-wild (ABAW)
Competition, held in conjunction with IEEE International Conference on Computer
Vision and Pattern Recognition (CVPR), 2022. The 3rd ABAW Competition is a
continuation of the Competitions held at ICCV 2021, IEEE FG 2020 and IEEE CVPR
2017 Conferences, and aims at automatically analyzing affect. This year the
Competition encompasses four Challenges: i) uni-task Valence-Arousal
Estimation, ii) uni-task Expression Classification, iii) uni-task Action Unit
Detection, and iv) Multi-Task-Learning. All the 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 in terms of valence-arousal,
expressions and action units. In this paper, we present the four Challenges,
with the utilized Competition corpora, we outline the evaluation metrics and
present the baseline systems along with their obtained results.
