62 citations · 114 across the 8 of their papers we have counts for
8 papers · 1 filter
Feature-level and Model-level Audiovisual Fusion for Emotion Recognition in the Wild
Jie Cai, Zibo Meng, Ahmed Shehab Khan +6
Emotion recognition plays an important role in human-computer interaction (HCI) and has been extensively studied for decades. Although tremendous improvements have been achieved fo…
Probabilistic Attribute Tree in Convolutional Neural Networks for Facial Expression Recognition
Jie Cai, Zibo Meng, Ahmed Shehab Khan +3
In this paper, we proposed a novel Probabilistic Attribute Tree-CNN (PAT-CNN) to explicitly deal with the large intra-class variations caused by identity-related attributes, e.g.,…
Island Loss for Learning Discriminative Features in Facial Expression Recognition
Jie Cai, Zibo Meng, Ahmed Shehab Khan +3
Over the past few years, Convolutional Neural Networks (CNNs) have shown promise on facial expression recognition. However, the performance degrades dramatically under real-world s…
Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
Shizhong Han, Zibo Meng, Ahmed Shehab Khan +1
Recognizing facial action units (AUs) from spontaneous facial expressions is still a challenging problem. Most recently, CNNs have shown promise on facial AU recognition. However,…
Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition
Shizhong Han, Zibo Meng, Zhiyuan Li +4
Recognizing facial action units (AUs) during spontaneous facial displays is a challenging problem. Most recently, Convolutional Neural Networks (CNNs) have shown promise for facial…
Improving Speech Related Facial Action Unit Recognition by Audiovisual Information Fusion
Zibo Meng, Shizhong Han, Ping Liu +1
It is challenging to recognize facial action unit (AU) from spontaneous facial displays, especially when they are accompanied by speech. The major reason is that the information is…