This article presents our results for the sixth Affective Behavior Analysis in-the-wild (ABAW)
competition. To improve the trustworthiness of facial analysis, we study the possibility of …

In this paper, we describe the results of the HSEmotion team in two tasks of the seventh
Affective Behavior Analysis in-the-wild (ABAW) competition, namely, multi-task learning for …

This article presents our results for the sixth Affective Behavior Analysis in-the-wild (ABAW)
competition. To improve the trustworthiness of facial analysis we study the possibility of …

In this article, the pre-trained convolutional networks from the EmotiEffNet family for frame-
level feature extraction are used for downstream emotion analysis tasks from the fifth …

Facial affect analysis is essential for understanding human expressions and behaviors,
encompassing action unit (AU) detection, expression (EXPR) recognition, and valence …

Facial affect analysis remains a challenging task with its setting transitioned from lab-
controlled to in-the-wild situations. In this paper, we present novel frameworks to handle the …

This work has been initiated for the 2nd Affective Behavior Analysis in-the-wild (ABAW 2021)
competition. We train a unified deep learning model on multi-databases to perform two …

In this article, the results of our team for the fifth Affective Behavior Analysis in-the-wild
(ABAW) competition are presented. The usage of the pre-trained convolutional networks …

In this paper, we consider the problem of real-time video-based facial emotion analytics,
namely, facial expression recognition, prediction of valence and arousal and detection of …

In this paper, we present the novel multi-task EfficientNet model and its usage in the 4th
competition on Affective Behavior Analysis in-the-wild (ABAW). This model is trained for …