Deep facial expression recognition: A survey
With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …
challenging in-the-wild conditions and the recent success of deep learning techniques in …
Facial expression recognition using convolutional neural networks: state of the art
C Pramerdorfer, M Kampel - arXiv preprint arXiv:1612.02903, 2016 - arxiv.org
The ability to recognize facial expressions automatically enables novel applications in
human-computer interaction and other areas. Consequently, there has been active research …
human-computer interaction and other areas. Consequently, there has been active research …
Attention mechanism-based CNN for facial expression recognition
Facial expression recognition is a hot research topic and can be applied in many computer
vision fields, such as human–computer interaction, affective computing and so on. In this …
vision fields, such as human–computer interaction, affective computing and so on. In this …
Video-based emotion recognition using CNN-RNN and C3D hybrid networks
In this paper, we present a video-based emotion recognition system submitted to the EmotiW
2016 Challenge. The core module of this system is a hybrid network that combines recurrent …
2016 Challenge. The core module of this system is a hybrid network that combines recurrent …
Facial sentiment analysis using AI techniques: state-of-the-art, taxonomies, and challenges
With the advancements in machine and deep learning algorithms, the envision of various
critical real-life applications in computer vision becomes possible. One of the applications is …
critical real-life applications in computer vision becomes possible. One of the applications is …
Auto-FERNet: A facial expression recognition network with architecture search
Deep convolutional neural networks have achieved great success in facial expression
datasets both under laboratory conditions and in the wild. However, most of these related …
datasets both under laboratory conditions and in the wild. However, most of these related …
Facial expressions recognition for human–robot interaction using deep convolutional neural networks with rectified adam optimizer
DO Melinte, L Vladareanu - Sensors, 2020 - mdpi.com
The interaction between humans and an NAO robot using deep convolutional neural
networks (CNN) is presented in this paper based on an innovative end-to-end pipeline …
networks (CNN) is presented in this paper based on an innovative end-to-end pipeline …
Knowledge augmented deep neural networks for joint facial expression and action unit recognition
Facial expression and action units (AUs) represent two levels of descriptions of the facial
behavior. Due to the underlying facial anatomy and the need to form a meaningful coherent …
behavior. Due to the underlying facial anatomy and the need to form a meaningful coherent …
Automatic recognition of student engagement using deep learning and facial expression
Engagement is a key indicator of the quality of learning experience, and one that plays a
major role in developing intelligent educational interfaces. Any such interface requires the …
major role in developing intelligent educational interfaces. Any such interface requires the …
Deep reinforcement learning for robust emotional classification in facial expression recognition
For emotion classification in facial expression recognition (FER), the performance of both
traditional statistical methods and state-of-the-art deep learning methods are highly …
traditional statistical methods and state-of-the-art deep learning methods are highly …