Deep Facial Expression Recognition: A Survey [PDF]
IEEE Transactions on Affective Computing, 2018 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 various fields, deep neural networks have increasingly been leveraged to ...
Shan Li, Weihong Deng
semanticscholar +1 more source
Facial Expression Transfer Based on Conditional Generative Adversarial Networks
IEEE Access, 2023 With the development of computer vision and image transfer, facial expression transfer has been more and more widespread applications. But there are still some problems, such as lack of realistic expression, poor retention of facial identity features and
Yang Fan +3 more
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Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition [PDF]
IEEE Transactions on Image Processing, 2019 Occlusion and pose variations, which can change facial appearance significantly, are two major obstacles for automatic Facial Expression Recognition (FER). Though automatic FER has made substantial progresses in the past few decades, occlusion-robust and
K. Wang +4 more
semanticscholar +1 more source
Cascade EF-GAN: Progressive Facial Expression Editing With Local Focuses [PDF]
Computer Vision and Pattern Recognition, 2020 Recent advances in Generative Adversarial Nets (GANs) have shown remarkable improvements for facial expression editing. However, current methods are still prone to generate artifacts and blurs around expression-intensive regions, and often introduce ...
R. Wu +3 more
semanticscholar +1 more source
ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition
Frontiers in Robotics and AI, 2022 The ability of a robot to generate appropriate facial expressions is a key aspect of perceived sociability in human-robot interaction. Yet many existing approaches rely on the use of a set of fixed, preprogrammed joint configurations for expression ...
Niyati Rawal +8 more
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First report of generalized face processing difficulties in möbius sequence. [PDF]
, 2013 Reverse simulation models of facial expression recognition suggest that we recognize the emotions of others by running implicit motor programmes responsible for the production of that expression.
A Todorov +55 more
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Artificial Neural Network Based Ensemble Approach for Multicultural Facial Expressions Analysis
IEEE Access, 2020 Facial expressions convey exhaustive information about human emotions and the most interactive way of social collaborations, despite differences in ethnicity, culture, and geography. Due to cultural differences, the variations in facial structure, facial
Ghulam Ali +7 more
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Racial Identity-Aware Facial Expression Recognition Using Deep Convolutional Neural Networks
Applied Sciences, 2021 Multi-culture facial expression recognition remains challenging due to cross cultural variations in facial expressions representation, caused by facial structure variations and culture specific facial characteristics.
Muhammad Sohail +7 more
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Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network [PDF]
Italian National Conference on Sensors, 2019 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.
Shervin Minaee, AmirAli Abdolrashidi
semanticscholar +1 more source
Hybrid Approach for Facial Expression Recognition Using Convolutional Neural Networks and SVM
Applied Sciences, 2022 Facial expression recognition is very useful for effective human–computer interaction, robot interfaces, and emotion-aware smart agent systems. This paper presents a new framework for facial expression recognition by using a hybrid model: a combination ...
Jin-Chul Kim +4 more
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