In recent years, vision transformers have been introduced into face
reco...
Deep neural networks are vulnerable to universal adversarial perturbatio...
In many real-world applications, face recognition models often degenerat...
Structured reconstruction is a non-trivial dense prediction problem, whi...
Although face recognition has made impressive progress in recent years, ...
In this paper, we delve into semi-supervised 2D human pose estimation. T...
Out-of-distribution (OOD) detection methods assume that they have test g...
Although deep learning has significantly improved Face Recognition (FR),...
Recently, great progress has been made in single-image super-resolution
...
Learning with noisy labels is a vital topic for practical deep learning ...
Facial expression recognition (FER) is a challenging problem because the...
Noisy label Facial Expression Recognition (FER) is more challenging than...
Due to the lack of diversity of datasets, the generalization ability of ...
Convolutional neural network based face forgery detection methods have
a...
With the emergence of GAN, face forgery technologies have been heavily
a...
In this paper, we aim to improve the performance of in-the-wild Facial
E...
Domain adaptation aims to leverage a labeled source domain to learn a
cl...
Despite great progress in face recognition tasks achieved by deep convol...
Deep face recognition has achieved great success due to large-scale trai...
While convenient in daily life, face recognition technologies also raise...
We introduce the Oracle-MNIST dataset, comprising of 28×28 grayscale
ima...
Oracle bone script is the earliest-known Chinese writing system of the S...
Although deep face recognition has achieved impressive progress in recen...
Video Question Answering (VideoQA) aims to answer natural language quest...
With increasing appealing to privacy issues in face recognition, federat...
As more and more people begin to wear masks due to current COVID-19 pand...
Although vanilla Convolutional Neural Network (CNN) based detectors can
...
Face photo-sketch synthesis and recognition has many applications in dig...
Recently there has been great interests of Transformer not only in NLP b...
Recent domain adaptation methods have demonstrated impressive improvemen...
In this paper, the Point Adversarial Self Mining (PASM) approach, a simp...
Much of the work on automatic facial expression recognition relies on
da...
Deep learning technique has dramatically boosted the performance of face...
In this paper, we target on advancing the performance in facial expressi...
Face recognition has achieved great success in the last five years due t...
Racial equality is an important theme of international human rights law,...
In order to make facial features more discriminative, some new models ha...
The Deep neural networks (DNNs) have achieved great success on a variety...
Attention has become more attractive in person reidentification (ReID) a...
In zero-shot image retrieval (ZSIR) task, embedding learning becomes mor...
Datasets play an important role in the progress of facial expression
rec...
Deep metric learning, which learns discriminative features to process im...
Deep metric learning has been widely applied in many computer vision tas...
Despite of the progress achieved by deep learning in face recognition (F...
Recently, learning discriminative features to improve the recognition
pe...
The performance of face detectors has been largely improved with the
dev...
Deep embedding learning becomes more attractive for discriminative featu...
With the transition of facial expression recognition (FER) from
laborato...
Driven by graphics processing units (GPUs), massive amounts of annotated...
Deep domain adaption has emerged as a new learning technique to address ...