2 code implementations • IEEE Transactions on Affective Computing 2022 • Savchenko A.V., Savchenko L.V., Makarov I
It is shown that the resulting facial features can be used for fast simultaneous prediction of students’ engagement levels (from disengaged to highly engaged), individual emotions (happy, sad, etc.,) and group-level affect (positive, neutral or negative).
Ranked #5 on Facial Expression Recognition (FER) on AffectNet
2 code implementations • CVPR Workshop 2022 • Savchenko A.V.
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 action unit points.
2 code implementations • 31 Mar 2021 • Savchenko A.V.
Moreover, it is shown that the usage of our neural network as a feature extractor of facial regions in video frames and concatenation of several statistical functions (mean, max, etc.)