2.2k citations · 6.6k across the 54 of their papers we have counts for
54 papers
Survey on Deep Face Restoration: From Non-blind to Blind and Beyond
Wenjie Li, Mei Wang, Kai Zhang +6
Face restoration (FR) is a specialized field within image restoration that aims to recover low-quality (LQ) face images into high-quality (HQ) face images. Recent advances in deep…
SwinFace: A Multi-task Transformer for Face Recognition, Expression Recognition, Age Estimation and Attribute Estimation
Lixiong Qin, Mei Wang, Chao Deng +4
In recent years, vision transformers have been introduced into face recognition and analysis and have achieved performance breakthroughs. However, most previous methods generally t…
Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation
Xuannan Liu, Yaoyao Zhong, Yuhang Zhang +2
Deep neural networks are vulnerable to universal adversarial perturbation (UAP), an instance-agnostic perturbation capable of fooling the target model for most samples. Compared to…
Adaptive Face Recognition Using Adversarial Information Network
Mei Wang, Weihong Deng
In many real-world applications, face recognition models often degenerate when training data (referred to as source domain) are different from testing data (referred to as target d…
Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attention
Linzhi Huang, Mei Wang, Jiahao Liang +5
Although face recognition has made impressive progress in recent years, we ignore the racial bias of the recognition system when we pursue a high level of accuracy. Previous work f…
Unsupervised Evaluation of Out-of-distribution Detection: A Data-centric Perspective
Yuhang Zhang, Weihong Deng, Liang Zheng
Out-of-distribution (OOD) detection methods assume that they have test ground truths, i.e., whether individual test samples are in-distribution (IND) or OOD. However, in the real w…
Semi-Supervised 2D Human Pose Estimation Driven by Position Inconsistency Pseudo Label Correction Module
Linzhi Huang, Yulong Li, Hongbo Tian +4
In this paper, we delve into semi-supervised 2D human pose estimation. The previous method ignored two problems: (i) When conducting interactive training between large model and li…
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,…
Model and Data Agreement for Learning with Noisy Labels
Yuhang Zhang, Weihong Deng, Xingchen Cui +3
Learning with noisy labels is a vital topic for practical deep learning as models should be robust to noisy open-world datasets in the wild. The state-of-the-art noisy label learni…
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network
Wenjie Li, Juncheng Li, Guangwei Gao +4
Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss…
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…
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…
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.…
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)…
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…
Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution
Wenjie Li, Juncheng Li, Guangwei Gao +3
Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction. However, the ca…
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher
Jing Jiang, Weihong Deng
In this paper, we aim to improve the performance of in-the-wild Facial Expression Recognition (FER) by exploiting semi-supervised learning. Large-scale labeled data and deep learni…
Cycle Label-Consistent Networks for Unsupervised Domain Adaptation
Mei Wang, Weihong Deng
Domain adaptation aims to leverage a labeled source domain to learn a classifier for the unlabeled target domain with a different distribution. Previous methods mostly match the di…
Deep face recognition with clustering based domain adaptation
Mei Wang, Weihong Deng
Despite great progress in face recognition tasks achieved by deep convolution neural networks (CNNs), these models often face challenges in real world tasks where training images g…
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
Yaoyao Zhong, Weihong Deng, Jiani Hu +3
Deep face recognition has achieved great success due to large-scale training databases and rapidly developing loss functions. The existing algorithms devote to realizing an ideal i…
OPOM: Customized Invisible Cloak towards Face Privacy Protection
Yaoyao Zhong, Weihong Deng
While convenient in daily life, face recognition technologies also raise privacy concerns for regular users on the social media since they could be used to analyze face images and…
Unsupervised Structure-Texture Separation Network for Oracle Character Recognition
Mei Wang, Weihong Deng, Cheng-Lin Liu
Oracle bone script is the earliest-known Chinese writing system of the Shang dynasty and is precious to archeology and philology. However, real-world scanned oracle data are rare a…
Meta Balanced Network for Fair Face Recognition
Mei Wang, Yaobin Zhang, Weihong Deng
Although deep face recognition has achieved impressive progress in recent years, controversy has arisen regarding discrimination based on skin tone, questioning their deployment in…
Oracle-MNIST: a Dataset of Oracle Characters for Benchmarking Machine Learning Algorithms
Mei Wang, Weihong Deng
We introduce the Oracle-MNIST dataset, comprising of 2828 grayscale images of 30,222 ancient characters from 10 categories, for benchmarking pattern classification, with p…