FaceRNET: a Facial Expression Intensity Estimation Network
- URL: http://arxiv.org/abs/2303.00180v3
- Date: Sat, 7 Oct 2023 13:35:56 GMT
- Title: FaceRNET: a Facial Expression Intensity Estimation Network
- Authors: Dimitrios Kollias, Andreas Psaroudakis, Anastasios Arsenos, Paraskevi
Theofilou
- Abstract summary: This paper presents our approach for Facial Expression Intensity Estimation from videos.
It includes two components: i) a representation extractor network that extracts various emotion descriptors from each videoframe; ii) a RNN that captures temporal information in the data, followed by a mask layer.
This approach has been tested on the Hume-Reaction dataset yielding excellent results.
- Score: 19.708950049023898
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: This paper presents our approach for Facial Expression Intensity Estimation
from videos. It includes two components: i) a representation extractor network
that extracts various emotion descriptors (valence-arousal, action units and
basic expressions) from each videoframe; ii) a RNN that captures temporal
information in the data, followed by a mask layer which enables handling
varying input video lengths through dynamic routing. This approach has been
tested on the Hume-Reaction dataset yielding excellent results.
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