Results 11 to 20 of about 6,456,473 (363)
Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition [PDF]
Computer Vision and Pattern Recognition, 2019 Face recognition has obtained remarkable progress in recent years due to the great improvement of deep convolutional neural networks (CNNs). However, deep CNNs are vulnerable to adversarial examples, which can cause fateful consequences in real-world ...
Yinpeng Dong +6 more
semanticscholar +3 more sources
Face ShapeNets for 3D Face Recognition
IEEE Access, 2023 In this paper, we present a deep learning-based method for 3D face recognition. Unlike some previous works, our process does not rely on face representation methods as a proxy step to be accepted by Convolutional Neural Networks (CNNs).
Marwa Jabberi +4 more
doaj +1 more source
SynFace: Face Recognition with Synthetic Data [PDF]
IEEE International Conference on Computer Vision, 2021 With the recent success of deep neural networks, remarkable progress has been achieved on face recognition. However, collecting large-scale real-world training data for face recognition has turned out to be challenging, especially due to the label noise ...
Haibo Qiu +5 more
semanticscholar +1 more source
CosFace: Large Margin Cosine Loss for Deep Face Recognition [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Face recognition has made extraordinary progress owing to the advancement of deep convolutional neural networks (CNNs). The central task of face recognition, including face verification and identification, involves face feature discrimination.
H. Wang +7 more
semanticscholar +1 more source
SphereFace: Deep Hypersphere Embedding for Face Recognition [PDF]
Computer Vision and Pattern Recognition, 2017 This paper addresses deep face recognition (FR) problem under open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably chosen metric space.
Weiyang Liu +5 more
semanticscholar +1 more source
ElasticFace: Elastic Margin Loss for Deep Face Recognition [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 Learning discriminative face features plays a major role in building high-performing face recognition models. The recent state-of-the-art face recognition solutions proposed to incorporate a fixed penalty margin on commonly used classification loss ...
Fadi Boutros +3 more
semanticscholar +1 more source
Effects of face masks on the appearance of emotional expressions and invariant characteristics
Open Psychology, 2021 Faces convey a lot of information about a person. However, the usage of face masks occludes important parts of the face. There is already information that face masks alter the processing of variable characteristics such as emotional expressions and the ...
Lau Wee Kiat, Huckauf Anke
doaj +1 more source
CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition [PDF]
Computer Vision and Pattern Recognition, 2020 As an emerging topic in face recognition, designing margin-based loss functions can increase the feature margin between different classes for enhanced discriminability.
Y. Huang +7 more
semanticscholar +1 more source
Misalignment-Robust Face Recognition [PDF]
IEEE Transactions on Image Processing, 2008 Subspace learning techniques for face recognition have been widely studied in the past three decades. In this paper, we study the problem of general subspace-based face recognition under the scenarios with spatial misalignments and/or image occlusions.
Yan, S. +4 more
openaire +2 more sources
A Comprehensive Survey on Face Quality Detection in a Video Frame [PDF]
E3S Web of Conferences, 2023 The correctness of the generated face data, which is impacted by a number of variables, significantly affects how well face analysis and recognition systems perform.
Bhuvaneshwari T. +4 more
doaj +1 more source