Age classification with deep learning face representation
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-4646-5
Abstract: Automatic age estimation from facial images is challenging not only for computers, but also for humans in some cases. Therefore, coarse age groups such as children, teen age, adult and senior adult are considered in… read more here.
Keywords: age classification; age; face representation; deep learning ... See more keywords
OTFace: Hard Samples Guided Optimal Transport Loss for Deep Face Representation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2022.3230331
Abstract: Face representation in the wild is extremely hard due to the large scale face variations. Some deep convolutional neural networks (CNNs) have been developed to learn discriminative feature by designing properly margin-based losses, which perform… read more here.
Keywords: samples guided; face; feature; face representation ... See more keywords
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs
Sign Up to like & getrecommendations! Published in 2020 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2020.3034267
Abstract: Although Generative Adversarial Networks (GANs) have made significant progress in face synthesis, there lacks enough understanding of what GANs have learned in the latent representation to map a randomly sampled code to a photo-realistic face… read more here.
Keywords: face representation; representation learned; disentangled face; face ... See more keywords