Deep Face Recognition: A Survey
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DOI: 10.1016/j.neucom.2020.10.081
Abstract: Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction. This emerging technique has reshaped the research landscape of face recognition (FR) since 2014, launched by the breakthroughs… read more here.
Keywords: face; deep face; recognition survey; face recognition ... See more keywords
Frankenstein: Learning Deep Face Representations Using Small Data
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DOI: 10.1109/tip.2017.2756450
Abstract: Deep convolutional neural networks have recently proven extremely effective for difficult face recognition problems in uncontrolled settings. To train such networks, very large training sets are needed with millions of labeled images. For some applications,… read more here.
Keywords: learning deep; deep face; frankenstein learning; large training ... See more keywords
Class-Variant Margin Normalized Softmax Loss for Deep Face Recognition
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.3017528
Abstract: In deep face recognition, the commonly used softmax loss and its newly proposed variations are not yet sufficiently effective to handle the class imbalance and softmax saturation issues during the training process while extracting discriminative… read more here.
Keywords: deep face; margin; face recognition; class ... See more keywords