Exploring Facial Expression Recognition through Semi-Supervised Pre-training and Temporal Modeling
Abstract Facial Expression Recognition (FER) plays a crucial role in computer vision and
finds extensive applications across various fields. This paper aims to present our approach …
finds extensive applications across various fields. This paper aims to present our approach …
A survey of face recognition
X Wang, J Peng, S Zhang, B Chen, Y Wang… - arXiv preprint arXiv …, 2022 - arxiv.org
Recent years witnessed the breakthrough of face recognition with deep convolutional neural
networks. Dozens of papers in the field of FR are published every year. Some of them were …
networks. Dozens of papers in the field of FR are published every year. Some of them were …
Exploring large-scale unlabeled faces to enhance facial expression recognition
Abstract Facial Expression Recognition (FER) is an important task in computer vision and
has wide applications in many fields. In this paper, we introduce our approach to the fifth …
has wide applications in many fields. In this paper, we introduce our approach to the fifth …
SVFAP: Self-supervised video facial affect perceiver
Video-based facial affect analysis has recently attracted increasing attention owing to its
critical role in human-computer interaction. Previous studies mainly focus on developing …
critical role in human-computer interaction. Previous studies mainly focus on developing …
Revisiting self-supervised contrastive learning for facial expression recognition
The success of most advanced facial expression recognition works relies heavily on large-
scale annotated datasets. However, it poses great challenges in acquiring clean and …
scale annotated datasets. However, it poses great challenges in acquiring clean and …
Learning 3d face reconstruction from the cycle-consistency of dynamic faces
W Yang, Y Zhao, B Yang, J Shen - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reconstructinga 3D face from a single image is a crucial task in numerous multimedia
applications. Face images with ground-truth 3D face shapes are scarce, so unsupervised …
applications. Face images with ground-truth 3D face shapes are scarce, so unsupervised …
Pose-disentangled contrastive learning for self-supervised facial representation
Self-supervised facial representation has recently attracted increasing attention due to its
ability to perform face understanding without relying on large-scale annotated datasets …
ability to perform face understanding without relying on large-scale annotated datasets …
An efficient attribute-preserving framework for face swapping
By leveraging deep neural networks, recent face swapping techniques have performed
admirably in generating faces that maintain consistent identities. Nevertheless, while these …
admirably in generating faces that maintain consistent identities. Nevertheless, while these …
Multimodal disentanglement variational autoencoders for zero-shot cross-modal retrieval
Zero-Shot Cross-Modal Retrieval (ZS-CMR) has recently drawn increasing attention as it
focuses on a practical retrieval scenario, ie, the multimodal test set consists of unseen …
focuses on a practical retrieval scenario, ie, the multimodal test set consists of unseen …
Emotic masked autoencoder with attention fusion for facial expression recognition
B Nguyen-Xuan, T Nguyen-Hoang, TH Nguyen… - arXiv preprint arXiv …, 2024 - arxiv.org
Facial Expression Recognition (FER) is a critical task within computer vision with diverse
applications across various domains. Addressing the challenge of limited FER datasets …
applications across various domains. Addressing the challenge of limited FER datasets …