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20172022
most citedIncremental Boosting Convolutional Neural Network for Facial Action Unit Recognition

62 citations · 150 across the 12 of their papers we have counts for

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9 papers · 1 filter

cs.CV2023

Defense against Adversarial Cloud Attack on Remote Sensing Salient Object Detection

Huiming Sun, Lan Fu, Jinlong Li +5

Detecting the salient objects in a remote sensing image has wide applications for the interdisciplinary research. Many existing deep learning methods have been proposed for Salient…

cs.CV20198 cited

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…

cs.CV201820 cited

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.,…

cs.CV201713 cited

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…

cs.CV201762 cited

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,…

cs.CV20174 cited

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…