Facenet2expnet: Regularizing a deep face recognition net for expression recognition
Relatively small data sets available for expression recognition research make the training of
deep networks very challenging. Although fine-tuning can partially alleviate the issue, the …
deep networks very challenging. Although fine-tuning can partially alleviate the issue, the …
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 …
Deep pain: Exploiting long short-term memory networks for facial expression classification
Pain is an unpleasant feeling that has been shown to be an important factor for the recovery
of patients. Since this is costly in human resources and difficult to do objectively, there is the …
of patients. Since this is costly in human resources and difficult to do objectively, there is the …
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 …
Dpcnet: Dual path multi-excitation collaborative network for facial expression representation learning in videos
Current works of facial expression learning in video consume significant computational
resources to learn spatial channel feature representations and temporal relationships. To …
resources to learn spatial channel feature representations and temporal relationships. To …
A compact deep learning model for robust facial expression recognition
In this paper, we propose a compact frame-based facial expression recognition framework
for facial expression recognition which achieves very competitive performance with respect …
for facial expression recognition which achieves very competitive performance with respect …
Generalized nonconvex nonsmooth low-rank minimization
As surrogate functions of L_0-norm, many nonconvex penalty functions have been proposed
to enhance the sparse vector recovery. It is easy to extend these nonconvex penalty …
to enhance the sparse vector recovery. It is easy to extend these nonconvex penalty …
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 …
Multimodal emotion recognition fusion analysis adapting BERT with heterogeneous feature unification
S Lee, DK Han, H Ko - IEEE access, 2021 - ieeexplore.ieee.org
Human communication includes rich emotional content, thus the development of multimodal
emotion recognition plays an important role in communication between humans and …
emotion recognition plays an important role in communication between humans and …
Automated pain detection from facial expressions using facs: A review
Facial pain expression is an important modality for assessing pain, especially when the
patient's verbal ability to communicate is impaired. The facial muscle-based action units …
patient's verbal ability to communicate is impaired. The facial muscle-based action units …