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.

本文介绍了第三届 ABAW 竞赛，该竞赛以自动情感分析为目标，并包括四个挑战：单任务价值 - 唤醒估计、单任务表情分类、单任务动作单元检测和多任务学习。在此基础上，我们概述了竞赛数据集、评估指标及基准系统。