Machine learning in computer vision: a review
INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability
to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is …
to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is …
Arcface: Additive angular margin loss for deep face recognition
One of the main challenges in feature learning using Deep Convolutional Neural Networks
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …
Partial fc: Training 10 million identities on a single machine
Face recognition has been an active and vital topic among computer vision community for a
long time. Previous researches mainly focus on loss functions used for facial feature …
long time. Previous researches mainly focus on loss functions used for facial feature …
Sub-center arcface: Boosting face recognition by large-scale noisy web faces
Margin-based deep face recognition methods (eg SphereFace, CosFace, and ArcFace)
have achieved remarkable success in unconstrained face recognition. However, these …
have achieved remarkable success in unconstrained face recognition. However, these …
Masked face recognition challenge: The insightface track report
During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which
poses a huge challenge to deep face recognition. In this workshop, we organize Masked …
poses a huge challenge to deep face recognition. In this workshop, we organize Masked …
Facial recognition for disease diagnosis using a deep learning convolutional neural network: a systematic review and meta-analysis
X Kong, Z Wang, J Sun, X Qi, Q Qiu… - Postgraduate Medical …, 2024 - academic.oup.com
Background With the rapid advancement of deep learning network technology, the
application of facial recognition technology in the medical field has received increasing …
application of facial recognition technology in the medical field has received increasing …
Global-local gcn: Large-scale label noise cleansing for face recognition
In the field of face recognition, large-scale web-collected datasets are essential for learning
discriminative representations, but they suffer from noisy identity labels, such as outliers and …
discriminative representations, but they suffer from noisy identity labels, such as outliers and …
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 …
Enhancing face recognition with self-supervised 3d reconstruction
Attributed to both the development of deep networks and abundant data, automatic face
recognition (FR) has quickly reached human-level capacity in the past few years. However …
recognition (FR) has quickly reached human-level capacity in the past few years. However …
Joint holistic and masked face recognition
With the widespread use of face masks due to the COVID-19 pandemic, accurate masked
face recognition has become more crucial than ever. While several studies have …
face recognition has become more crucial than ever. While several studies have …