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 …
Poster++: A simpler and stronger facial expression recognition network
J Mao, R Xu, X Yin, Y Chang, B Nie, A Huang… - Pattern Recognition, 2024 - Elsevier
The POSTER has achieved SOTA performance in facial expression recognition (FER) by
effectively combining facial landmarks and image features through its two-stream pyramid …
effectively combining facial landmarks and image features through its two-stream pyramid …
Learn from all: Erasing attention consistency for noisy label facial expression recognition
Abstract Noisy label Facial Expression Recognition (FER) is more challenging than
traditional noisy label classification tasks due to the inter-class similarity and the annotation …
traditional noisy label classification tasks due to the inter-class similarity and the annotation …
Transfer: Learning relation-aware facial expression representations with transformers
Facial expression recognition (FER) has received increasing interest in computer vision. We
propose the TransFER model which can learn rich relation-aware local representations. It …
propose the TransFER model which can learn rich relation-aware local representations. It …
SelfMatch: Robust semisupervised time‐series classification with self‐distillation
Over the years, a number of semisupervised deep‐learning algorithms have been proposed
for time‐series classification (TSC). In semisupervised deep learning, from the point of view …
for time‐series classification (TSC). In semisupervised deep learning, from the point of view …
Towards semi-supervised deep facial expression recognition with an adaptive confidence margin
Only parts of unlabeled data are selected to train models for most semi-supervised learning
methods, whose confidence scores are usually higher than the pre-defined threshold (ie, the …
methods, whose confidence scores are usually higher than the pre-defined threshold (ie, the …
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 …
[HTML][HTML] A comprehensive survey on deep facial expression recognition: challenges, applications, and future guidelines
Facial expression recognition (FER) is an emerging and multifaceted research topic.
Applications of FER in healthcare, security, safe driving, and so forth have contributed to the …
Applications of FER in healthcare, security, safe driving, and so forth have contributed to the …
Vision transformer with attentive pooling for robust facial expression recognition
Facial Expression Recognition (FER) in the wild is an extremely challenging task. Recently,
some Vision Transformers (ViT) have been explored for FER, but most of them perform …
some Vision Transformers (ViT) have been explored for FER, but most of them perform …
Self-supervised vision transformer-based few-shot learning for facial expression recognition
X Chen, X Zheng, K Sun, W Liu, Y Zhang - Information Sciences, 2023 - Elsevier
Facial expression recognition (FER) is embedded in many real-world human-computer
interaction tasks, such as online learning, depression recognition and remote diagnosis …
interaction tasks, such as online learning, depression recognition and remote diagnosis …