Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers
Speech is the most natural way of expressing ourselves as humans. It is only natural then to
extend this communication medium to computer applications. We define speech emotion …
extend this communication medium to computer applications. We define speech emotion …
Emoca: Emotion driven monocular face capture and animation
As 3D facial avatars become more widely used for communication, it is critical that they
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …
Distribution matching for heterogeneous multi-task learning: a large-scale face study
Multi-Task Learning has emerged as a methodology in which multiple tasks are jointly
learned by a shared learning algorithm, such as a DNN. MTL is based on the assumption …
learned by a shared learning algorithm, such as a DNN. MTL is based on the assumption …
Affect analysis in-the-wild: Valence-arousal, expressions, action units and a unified framework
Affect recognition based on subjects' facial expressions has been a topic of major research
in the attempt to generate machines that can understand the way subjects feel, act and react …
in the attempt to generate machines that can understand the way subjects feel, act and react …
Macro-and micro-expressions facial datasets: A survey
Automatic facial expression recognition is essential for many potential applications. Thus,
having a clear overview on existing datasets that have been investigated within the …
having a clear overview on existing datasets that have been investigated within the …
Expression, affect, action unit recognition: Aff-wild2, multi-task learning and arcface
Affective computing has been largely limited in terms of available data resources. The need
to collect and annotate diverse in-the-wild datasets has become apparent with the rise of …
to collect and annotate diverse in-the-wild datasets has become apparent with the rise of …
Estimation of continuous valence and arousal levels from faces in naturalistic conditions
Facial affect analysis aims to create new types of human–computer interactions by enabling
computers to better understand a person's emotional state in order to provide ad hoc help …
computers to better understand a person's emotional state in order to provide ad hoc help …
Ferv39k: A large-scale multi-scene dataset for facial expression recognition in videos
Current benchmarks for facial expression recognition (FER) mainly focus on static images,
while there are limited datasets for FER in videos. It is still ambiguous to evaluate whether …
while there are limited datasets for FER in videos. It is still ambiguous to evaluate whether …
Context-aware emotion recognition networks
Traditional techniques for emotion recognition have focused on the facial expression
analysis only, thus providing limited ability to encode context that comprehensively …
analysis only, thus providing limited ability to encode context that comprehensively …
M3er: Multiplicative multimodal emotion recognition using facial, textual, and speech cues
We present M3ER, a learning-based method for emotion recognition from multiple input
modalities. Our approach combines cues from multiple co-occurring modalities (such as …
modalities. Our approach combines cues from multiple co-occurring modalities (such as …