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FERAtt: Facial Expression Recognition with Attention Net
[article]
2019
arXiv
pre-print
We present a new end-to-end network architecture for facial expression recognition with an attention model. It focuses attention in the human face and uses a Gaussian space representation for expression recognition. We devise this architecture based on two fundamental complementary components: (1) facial image correction and attention and (2) facial expression representation and classification. The first component uses an encoder-decoder style network and a convolutional feature extractor that
arXiv:1902.03284v1
fatcat:r4f5pkiq4je6bgvzcb24nj5lzq