A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
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 …
Deep learning for human affect recognition: Insights and new developments
Automatic human affect recognition is a key step towards more natural human-computer
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
Facial expression recognition using residual masking network
Automatic facial expression recognition (FER) has gained much attention due to its
applications in human-computer interaction. Among the approaches to improve FER tasks …
applications in human-computer interaction. Among the approaches to improve FER tasks …
Island loss for learning discriminative features in facial expression recognition
Over the past few years, Convolutional Neural Networks (CNNs) have shown promise on
facial expression recognition. However, the performance degrades dramatically under real …
facial expression recognition. However, the performance degrades dramatically under real …
Frame attention networks for facial expression recognition in videos
The video-based facial expression recognition aims to classify a given video into several
basic emotions. How to integrate facial features of individual frames is crucial for this task. In …
basic emotions. How to integrate facial features of individual frames is crucial for this task. In …
Landmark guidance independent spatio-channel attention and complementary context information based facial expression recognition
Attention based convolutional neural networks (CNNs) for facial expression recognition
(FER) apply attention that is uniform across either spatial dimensions or channel dimensions …
(FER) apply attention that is uniform across either spatial dimensions or channel dimensions …
A survey of ai-based facial emotion recognition: Features, ml & dl techniques, age-wise datasets and future directions
Facial expressions are mirrors of human thoughts and feelings. It provides a wealth of social
cues to the viewer, including the focus of attention, intention, motivation, and emotion. It is …
cues to the viewer, including the focus of attention, intention, motivation, and emotion. It is …
Expression snippet transformer for robust video-based facial expression recognition
Although Transformer can be powerful for modeling visual relations and describing
complicated patterns, it could still perform unsatisfactorily for video-based facial expression …
complicated patterns, it could still perform unsatisfactorily for video-based facial expression …
Spatio-temporal convolutional features with nested LSTM for facial expression recognition
In this paper, we propose a novel end-to-end architecture termed Spatio-Temporal
Convolutional features with Nested LSTM (STC-NLSTM), which learns the muti-level …
Convolutional features with Nested LSTM (STC-NLSTM), which learns the muti-level …