Human affect recognition is an essential part of natural human-computer
interaction. However, current methods are still in their infancy, especially
for in-the-wild data. In this work, we introduce our submission to the
Affective Behavior Analysis in-the-wild (ABAW) 2020 competition. We propose a
two-stream aural-visual analysis model to recognize affective behavior from
videos. Audio and image streams are first processed separately and fed into a
convolutional neural network. Instead of applying recurrent architectures for
temporal analysis we only use temporal convolutions. Furthermore, the model is
given access to additional features extracted during face-alignment. At
training time, we exploit correlations between different emotion
representations to improve performance. Our model achieves promising results on
the challenging Aff-Wild2 database.

本文介绍了我们提交到 ABAW 2020 竞赛的两条流声音视觉分析模型来识别视频中的情感行为。该模型分别处理音频和图像流，并使用卷积神经网络进行分析，同时使用人脸对齐期间提取的附加功能。在训练期间，利用不同情感表达之间的相关性来提高性能。通过在 Aff-Wild2 数据库上的实验，我们的模型取得了有希望的结果。

野外双流感性音视频分析

Two-Stream Aural-Visual Affect Analysis in the Wild

The Affective Behavior Analysis in-the-wild (ABAW) 2020 Competition is the
first Competition aiming at automatic analysis of the three main behavior tasks
of valence-arousal estimation, basic expression recognition and action unit
detection. It is split into three Challenges, each one addressing a respective
behavior task. For the Challenges, we provide a common benchmark database,
Aff-Wild2, which is a large scale in-the-wild database and the first one
annotated for all these three tasks. In this paper, we describe this
Competition, to be held in conjunction with the IEEE Conference on Face and
Gesture Recognition, May 2020, in Buenos Aires, Argentina. We present the three
Challenges, with the utilized Competition corpora. We outline the evaluation
metrics, present both the baseline system and the top-3 performing teams'
methodologies per Challenge and finally present their obtained results. More
information regarding the Competition, the leaderboard of each Challenge and
details for accessing the utilized database, are provided in the Competition
site:
this http URL

这篇论文介绍了 Affective Behavior Analysis in-the-wild (ABAW) 2020 Competition，它是第一个旨在自动分析情感行为的比赛，分为三个挑战，分别是估计情感价值 - 唤醒、基本表情识别和动作单元检测。其中，Aff-Wild2 是一个大规模的真实环境数据库，是第一个为所有这三项任务注释的数据库。