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Robust Facial Expression Recognition with Convolutional Visual Transformers [article]

Fuyan Ma, Bin Sun, Shutao Li
2021 arXiv   pre-print
Therefore, we propose Convolutional Visual Transformers to tackle FER in the wild by two main steps.  ...  Different from previous pure CNNs based methods, we argue that it is feasible and practical to translate facial images into sequences of visual words and perform expression recognition from a global perspective  ...  Therefore, we propose Convolutional Visual Transformers (CVT) for robust facial expression recognition in the wild.  ... 
arXiv:2103.16854v2 fatcat:q4nqmbvehfagzkvrb7p424yd6q

Subject independent facial expression recognition with robust face detection using a convolutional neural network

Masakazu Matsugu, Katsuhiko Mori, Yusuke Mitari, Yuji Kaneda
2003 Neural Networks  
We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network.  ...  To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance. q  ...  In Section 2, we introduce a modular convolutional network architecture for robust face detection and facial expression recognition involving module-based learning based on a variant of BP.  ... 
doi:10.1016/s0893-6080(03)00115-1 pmid:12850007 fatcat:7nmrdmgtqrfr7jhsalbjwoai7i

Improved Facial Expression Recognition Based on DWT Feature for Deep CNN

Ridha Bendjillali, Mohammed Beladgham, Khaled Merit, Abdelmalik Taleb-Ahmed
2019 Electronics  
Facial expression recognition (FER) has become one of the most important fields of research in pattern recognition.  ...  algorithm, the discrete wavelet transform (DWT), and deep convolutional neural network (CNN).  ...  facial expressions, with recognition accuracy of 98.5%-97.5% respectively.  ... 
doi:10.3390/electronics8030324 fatcat:dnjji46sazgxlnomhbgsvi2h6q

FERAtt: Facial Expression Recognition With Attention Net

Pedro D. Marrero Fernandez, Fidel A. Guerrero Pena, Tsang Ing Ren, Alexandre Cunha
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
We present a new end-to-end network architecture for facial expression recognition with an attention model.  ...  We compared results with the Pre-ActResNet18 baseline. Our experiments on these datasets have shown the superiority of our approach in recognizing facial expressions.  ...  The careful design of local to global feature learning with a convolution, pooling, and layered architecture produces a rich visual representation, making CNN a powerful tool for facial expression recognition  ... 
doi:10.1109/cvprw.2019.00112 dblp:conf/cvpr/Marrero-Fernandez19 fatcat:tl332ikpebbevajwbyi3gbekaa

Local Dominant Directional Symmetrical Coding Patterns for Facial Expression Recognition

Ying Tong, Rui Chen
2019 Computational Intelligence and Neuroscience  
Then, we encode the dominant direction information of facial expression texture by comparing each pixel's convolution values with the average strength of its belonging group and obtain LDDSCP-1 and LDDSCP  ...  in recognition rate and computational complexity.  ...  step of facial expression recognition.  ... 
doi:10.1155/2019/3587036 pmid:31217801 pmcid:PMC6537010 fatcat:n6mczhnmfzb2nkiaslybsbe5te

Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition

Liam Schoneveld, Alice Othmani, Hazem Abdelkawy
2021 Pattern Recognition Letters  
Moreover, our proposed visual facial expression feature extraction network outperforms state-of-the-art results on the AffectNet and Google Facial Expression Comparison datasets.  ...  In this paper, we propose a new deep learning-based approach for audio-visual emotion recognition.  ...  Powder is a video editing and sharing platform for gamers. https://powder.gg/ Supplementary Materials Supplementary material associated with this article can be found in the enclosed file.  ... 
doi:10.1016/j.patrec.2021.03.007 fatcat:k7xzwtqxr5cjxgsx7q3ssalpfa

FERAtt: Facial Expression Recognition with Attention Net [article]

Pedro D. Marrero Fernandez, Fidel A. Guerrero Peña, Tsang Ing Ren, Alexandre Cunha
2019 arXiv   pre-print
We present a new end-to-end network architecture for facial expression recognition with an attention model.  ...  We compared results with the PreActResNet18 baseline. Our experiments on these datasets have shown the superiority of our approach in recognizing facial expressions.  ...  The careful design of local to global feature learning with convolution, pooling, and layered architecture produces a rich visual representation, making CNN a powerful tool for facial expression recognition  ... 
arXiv:1902.03284v1 fatcat:r4f5pkiq4je6bgvzcb24nj5lzq

Illumination-robust face recognition based on deep convolutional neural networks architectures

Ridha Ilyas Bendjillali, Mohammed Beladgham, Khaled Merit, Abdelmalik Taleb-Ahmed
2020 Indonesian Journal of Electrical Engineering and Computer Science  
Finally, the comparison with the other methods on both databases shows the robustness and effectiveness of the proposed approach.  ...  <p><span>In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology.  ...  ACKNOWLEDGEMENTS This work is supported by a research project about design and implementation of a surveillance system based on biometric systems for the detection and recognition of individuals and abnormal  ... 
doi:10.11591/ijeecs.v18.i2.pp1015-1027 fatcat:l3ospwg2qnhztgsg4qnhpqigta

Empirical Investigation of Multimodal Sensors in Novel Deep Facial Expression Recognition In-the-Wild

Asad Ullah, Jing Wang, M. Shahid Anwar, Taeg Keun Whangbo, Yaping Zhu, Giuseppe Quero
2021 Journal of Sensors  
The interest in the facial expression recognition (FER) is increasing day by day due to its practical and potential applications, such as human physiological interaction diagnosis and mental diseases detection  ...  This research work presents a novel framework and proposes an effective and robust solution for FER under an unconstrained environment.  ...  Acknowledgments The manuscript is funded with the fund of the Communication University China lab.  ... 
doi:10.1155/2021/8893661 fatcat:xb37qfpxrjhc7e5bp2j4r4mzbe

Chinese Tone Recognition Based on 3D Dynamic Muscle Information

JianRong Wang, Li Wan, Ju Zhang, Qiang Fang, Fan Yang, Jing Hu
2020 Discrete Dynamics in Nature and Society  
To advance the study of lip-reading recognition in accordance with Chinese pronunciation norms, we carefully investigated Mandarin tone recognition based on visual information, in contrast to that of the  ...  In this paper, we mainly studied the vowel tonal transformation in Chinese pronunciation and designed a lightweight skipping convolution network framework (SCNet).  ...  Pixel-based methods extract visual features from the image directly or after some preprocessing and transformation. Yuhas et al.  ... 
doi:10.1155/2020/5476896 doaj:0b060427e5a145778d232ea3315755d2 fatcat:gf54gtycyvdijnkufwakvfclvi

Imitation as a communication tool for online facial expression learning and recognition

S Boucenna, P Gaussier, P Andry, L Hafemeister
2010 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems  
Our starting point was a mathematical model showing that if the baby uses a sensory motor architecture for the recognition of the facial expression then the parents must imitate the baby facial expression  ...  the facial expression 'sadness', 'happiness'...).  ...  Soussignan for their help to calibrate the robot facial expressions and P. Canet for the design of the robot head. Many thanks also to L.  ... 
doi:10.1109/iros.2010.5650357 dblp:conf/iros/BoucennaGAH10 fatcat:aly6inskmjbajgcdip4th22fsm

HOG-ESRs Face Emotion Recognition Algorithm Based on HOG Feature and ESRs Method

Yuanchang Zhong, Lili Sun, Chenhao Ge, Huilian Fan
2021 Symmetry  
At present, although convolutional neural network has achieved great success in face emotion recognition algorithms, it has a rising space in effective feature extraction and recognition accuracy.  ...  As we all know, there are many ways to express emotions.  ...  Author Contributions: Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, visualization, Writing-Original draft preparation, L.S. and C.G.; resources, Writing-Review  ... 
doi:10.3390/sym13020228 fatcat:efzsm7qs55ejfehkwhwdw3vecq

Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

Shervin Minaee, Mehdi Minaei, Amirali Abdolrashidi
2021 Sensors  
In recent years, several works proposed an end-to-end framework for facial expression recognition using deep learning models.  ...  Facial expression recognition has been an active area of research over the past few decades, and it is still challenging due to the high intra-class variation.  ...  Acknowledgments: We express our gratitude to the people at University of Washington Graphics and Imaging Lab (GRAIL) for providing us with access to the FERG database.  ... 
doi:10.3390/s21093046 pmid:33925371 fatcat:awrun3leqrfcri5zneikh4v4rq

Facial Expression Recognition Research Based on Deep Learning [article]

Yongpei Zhu, Hongwei Fan, Kehong Yuan
2019 arXiv   pre-print
expression recognition convolution neural network forms a detector for the specific facial action unit.  ...  Therefore, we have verified that the convolution neural network has formed a detector for the facial Action unit in the training process to realize the expression recognition.  ...  feature maps with deconvolution visualization, and explain the learning mechanism of CNN with the help of expression classification.  ... 
arXiv:1904.09737v3 fatcat:wshlfqk4ufhfvogce4ybgplbye

Deep Multi-Facial patches Aggregation Network for Expression Classification from Face Images [article]

Amine Djerghri, Ahmed Rachid Hazourli, Alice Othmani
2020 arXiv   pre-print
In this paper, we investigate HCI via a deep multi-facial patches aggregation network for Face Expression Recognition (FER).  ...  Human prone to naturally interact with computers face-to-face. Human Expressions is an important key to better link human and computers.  ...  Conclusion and future works In this paper, we propose a Multi-Facial Patchesbased Convolutional Neural Networks (MFP-CNN) for Face Expression Recognition (FER).  ... 
arXiv:1909.10305v2 fatcat:5u3rmduh6bhshhfw7i5mvpnrm4
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