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: A review of trends and techniques
Facial Expression Recognition (FER) is presently the aspect of cognitive and affective
computing with the most attention and popularity, aided by its vast application areas. Several …
computing with the most attention and popularity, aided by its vast application areas. Several …
Learning facial expression and body gesture visual information for video emotion recognition
Recent research has shown that facial expressions and body gestures are two significant
implications in identifying human emotions. However, these studies mainly focus on …
implications in identifying human emotions. However, these studies mainly focus on …
Facial expressions recognition with multi-region divided attention networks for smart education cloud applications
In recent years, the electronic devices and wireless network are seen everywhere,
generating a massive amount of online surveillance video data that can be applied to …
generating a massive amount of online surveillance video data that can be applied to …
Spatial-temporal graphs plus transformers for geometry-guided facial expression recognition
Facial expression recognition (FER) is of great interest to the current studies of human-
computer interaction. In this paper, we propose a novel geometry-guided facial expression …
computer interaction. In this paper, we propose a novel geometry-guided facial expression …
LQGDNet: A local quaternion and global deep network for facial depression recognition
Recent visual-based depression recognition methods mostly use hand-crafted features with
information lost in color channels, or deep network features with a limited performance from …
information lost in color channels, or deep network features with a limited performance from …
Video multimodal emotion recognition based on Bi-GRU and attention fusion
RH Huan, J Shu, SL Bao, RH Liang, P Chen… - Multimedia Tools and …, 2021 - Springer
A video multimodal emotion recognition method based on Bi-GRU and attention fusion is
proposed in this paper. Bidirectional gated recurrent unit (Bi-GRU) is applied to improve the …
proposed in this paper. Bidirectional gated recurrent unit (Bi-GRU) is applied to improve the …
STRAN: Student expression recognition based on spatio-temporal residual attention network in classroom teaching videos
Z Chen, M Liang, Z Xue, W Yu - Applied Intelligence, 2023 - Springer
In order to obtain the state of students' listening in class objectively and accurately, we can
obtain students' emotions through their expressions in class and cognitive feedback through …
obtain students' emotions through their expressions in class and cognitive feedback through …
Enhanced spatial-temporal learning network for dynamic facial expression recognition
W Gong, Y Qian, W Zhou, H Leng - Biomedical Signal Processing and …, 2024 - Elsevier
The recognition of dynamic facial expressions has received increasing attention since they
can better reflect the real expression process of emotion than a static image. However, due …
can better reflect the real expression process of emotion than a static image. However, due …
Stcam: Spatial-temporal and channel attention module for dynamic facial expression recognition
Capturing the dynamics of facial expression progression in video is an essential and
challenging task for facial expression recognition (FER). In this article, we propose an …
challenging task for facial expression recognition (FER). In this article, we propose an …