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20212023
most citedDisentangling Identity and Pose for Facial Expression Recognition

56 citations · 72 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.CV20231 cited

Dive into the Resolution Augmentations and Metrics in Low Resolution Face Recognition: A Plain yet Effective New Baseline

Xu Ling, Yichen Lu, Wenqi Xu +5

Although deep learning has significantly improved Face Recognition (FR), dramatic performance deterioration may occur when processing Low Resolution (LR) faces. To alleviate this,…

cs.CV202256 cited

Disentangling Identity and Pose for Facial Expression Recognition

Jing Jiang, Weihong Deng

Facial expression recognition (FER) is a challenging problem because the expression component is always entangled with other irrelevant factors, such as identity and head pose. In…

cs.CV20222 cited

DH-AUG: DH Forward Kinematics Model Driven Augmentation for 3D Human Pose Estimation

Linzhi Huang, Jiahao Liang, Weihong Deng

Due to the lack of diversity of datasets, the generalization ability of the pose estimator is poor. To solve this problem, we propose a pose augmentation solution via DH forward ki…

cs.CV2022

Exploring Disentangled Content Information for Face Forgery Detection

Jiahao Liang, Huafeng Shi, Weihong Deng

Convolutional neural network based face forgery detection methods have achieved remarkable results during training, but struggled to maintain comparable performance during testing.…

cs.CV2022

Identifying Rhythmic Patterns for Face Forgery Detection and Categorization

Jiahao Liang, Weihong Deng

With the emergence of GAN, face forgery technologies have been heavily abused. Achieving accurate face forgery detection is imminent. Inspired by remote photoplethysmography (rPPG)…

cs.CV20228 cited

Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition

Yuhang Zhang, Chengrui Wang, Xu Ling +1

Noisy label Facial Expression Recognition (FER) is more challenging than traditional noisy label classification tasks due to the inter-class similarity and the annotation ambiguity…