Analysing affective behavior in the second abaw2 competition
D Kollias, S Zafeiriou - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
Abstract The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the
second Competition-following the first very successful ABAW Competition held in …
second Competition-following the first very successful ABAW Competition held 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 …
Extended deep neural network for facial emotion recognition
DK Jain, P Shamsolmoali, P Sehdev - Pattern Recognition Letters, 2019 - Elsevier
Humans use facial expressions to show their emotional states. However, facial expression
recognition has remained a challenging and interesting problem in computer vision. In this …
recognition has remained a challenging and interesting problem in computer vision. In this …
Convolutional neural networks-an extensive arena of deep learning. A comprehensive study
N Singh, H Sabrol - Archives of Computational Methods in Engineering, 2021 - Springer
Deep learning is an evolving expanse of machine learning. Machine learning is observing
its neoteric span as deep learning is steadily becoming the pioneer in this field. With the …
its neoteric span as deep learning is steadily becoming the pioneer in this field. With the …
Hybrid deep neural networks for face emotion recognition
Abstract Deep Neural Networks (DNNs) outperform traditional models in numerous optical
recognition missions containing Facial Expression Recognition (FER) which is an imperative …
recognition missions containing Facial Expression Recognition (FER) which is an imperative …
Exploiting multi-cnn features in cnn-rnn based dimensional emotion recognition on the omg in-the-wild dataset
D Kollias, S Zafeiriou - IEEE Transactions on Affective …, 2020 - ieeexplore.ieee.org
This article presents a novel CNN-RNN based approach, which exploits multiple CNN
features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual …
features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual …
Multi-objective based spatio-temporal feature representation learning robust to expression intensity variations for facial expression recognition
Facial expression recognition (FER) is increasingly gaining importance in various emerging
affective computing applications. In practice, achieving accurate FER is challenging due to …
affective computing applications. In practice, achieving accurate FER is challenging due to …
CNN and LSTM-based emotion charting using physiological signals
Novel trends in affective computing are based on reliable sources of physiological signals
such as Electroencephalogram (EEG), Electrocardiogram (ECG), and Galvanic Skin …
such as Electroencephalogram (EEG), Electrocardiogram (ECG), and Galvanic Skin …
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 …
Emotion recognition in the wild from videos using images
This paper presents the implementation details of the proposed solution to the Emotion
Recognition in the Wild 2016 Challenge, in the category of video-based emotion …
Recognition in the Wild 2016 Challenge, in the category of video-based emotion …