Yingruo Fan

Yingruo Fan
The University of Hong Kong | HKU · Department of Computer Science

About

10
Publications
4,441
Reads
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979
Citations
Citations since 2017
10 Research Items
979 Citations
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2017201820192020202120222023050100150200
2017201820192020202120222023050100150200

Publications

Publications (10)
Article
Facial expression recognition (FER) is crucial for social communication. However, current studies present limitations when addressing facial expression difference due to demographic variation, e.g., race, gender, and age, etc. In this study, we first propose a deeply-supervised attention network (DSAN) to recognize human emotions based on facial im...
Article
The intensity estimation of facial action units (AUs) is challenging due to subtle changes in the person's facial appearance. Previous approaches mainly rely on probabilistic models or predefined rules for modeling co-occurrence relationships among AUs, leading to limited generalization. In contrast, we present a new learning framework that automat...
Article
Full-text available
Understanding demographic difference in facial expression of happiness has crucial implications on social communication. However, prior research on facial emotion expression has mostly focused on the effect of a single demographic factor (typically gender, race, or age), and is limited by the small image dataset collected in laboratory settings. Fi...
Preprint
The intensity estimation of facial action units (AUs) is challenging due to subtle changes in the person's facial appearance. Previous approaches mainly rely on probabilistic models or predefined rules for modeling co-occurrence relationships among AUs, leading to limited generalization. In contrast, we present a new learning framework that automat...
Conference Paper
Full-text available
Emotion recognition (ER) based on natural facial images/videos has been studied for some years and considered a comparatively hot topic in the field of affective computing. However, it remains a challenge to perform ER in the wild, given the noises generated from head pose, face deformation, and illumination variation. To address this challenge, mo...
Chapter
Facial expressions play an important role in conveying the emotional states of human beings. Recently, deep learning approaches have been applied to image recognition field due to the discriminative power of Convolutional Neural Network (CNN). In this paper, we first propose a novel Multi-Region Ensemble CNN (MRE-CNN) framework for facial expressio...
Preprint
Full-text available
Facial expressions play an important role in conveying the emotional states of human beings. Recently, deep learning approaches have been applied to image recognition field due to the discriminative power of Convolutional Neural Network (CNN). In this paper, we first propose a novel Multi-Region Ensemble CNN (MRE-CNN) framework for facial expressio...

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