Laser & Optoelectronics Progress, Volume. 56, Issue 24, 241505(2019)
Face Recognition Algorithm Based on Attribute-Driven Loss Function
To make the face recognition features learned from the convolutional neural network easier to identify, this paper improves the angular distance loss function A-Softmax by incorporating the facial attributes, such as gender, age, and race, into the training process. By using an attribute-driven loss function and regularizing the feature mapping with attribute proximity, the experimental result shows that more attribute-related discriminating features are learned by the proposed method. The improved algorithm has achieved good results in the face verification datasets, such as LFW, CFP, AgeDB, and MegaFace, verifying the effectiveness of the improved algorithm.
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Shen Li, Hansong Su, Gaohua Liu, Huihua Wu, Meng Wang. Face Recognition Algorithm Based on Attribute-Driven Loss Function[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241505
Category: Machine Vision
Received: Apr. 25, 2019
Accepted: Jun. 24, 2019
Published Online: Nov. 26, 2019
The Author Email: Liu Gaohua (suppig@126.com)