Deep face recognition: A survey
Mei Wang,Weihong Deng +1 more
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TLDR
A comprehensive review of the recent developments on deep face recognition can be found in this paper, covering broad topics on algorithm designs, databases, protocols, and application scenes, as well as the technical challenges and several promising directions.About:
This article is published in Neurocomputing.The article was published on 2021-03-14 and is currently open access. It has received 353 citations till now. The article focuses on the topics: Deep learning & Feature extraction.read more
Citations
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MORPH: A Longitudinal Image Database of Normal Adult Age-Progression.
Karl Ricanek,Tamirat Tesafaye +1 more
TL;DR: It is concluded that the problem of age-progression on face recognition (FR) is not unique to the algorithm used in this work, and the efficacy of this algorithm is evaluated against the variables of gender and racial origin.
References
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Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning
TL;DR: A novel pairwise similarity measure that advances existing models by i) expanding traditional linear projections into affine transformations and ii) fusing affine Mahalanobis distance and Cosine similarity by a data-driven combination is presented.
Proceedings Article
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
Jian Zhao,Lin Xiong,Panasonic Karlekar Jayashree,Jianshu Li,Fang Zhao,Zhecan Wang,Panasonic Sugiri Pranata,Panasonic Shengmei Shen,Shuicheng Yan,Jiashi Feng +9 more
TL;DR: Experimental results show that the proposed Dual-Agent Generative Adversarial Network (DA-GAN) model not only presents compelling perceptual results but also significantly outperforms state-of-the-arts on the large-scale and challenging NIST IJB-A unconstrained face recognition benchmark.
Proceedings ArticleDOI
End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning
TL;DR: This paper proposes a novel approach for photo-sketch generation, aiming to automatically transform face photos into detail-preserving personal sketches, and develops a fully convolutional network to learn the end-to-end photo-Sketch mapping.
Proceedings ArticleDOI
Learning Meta Face Recognition in Unseen Domains
TL;DR: This paper proposes a novel face recognition method via meta-learning named Meta Face Recognition (MFR), which synthesizes the source/target domain shift with a meta-optimization objective, which requires the model to learn effective representations not only on synthesized source domains but also on synthesizer target domains.
Proceedings ArticleDOI
Pose-Robust Face Recognition via Deep Residual Equivariant Mapping
TL;DR: Deep Residual Equivariant Mapping (DREAM) as mentioned in this paper is proposed to adaptively add residuals to the input deep representation to transform a profile face representation to a canonical pose.