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SARGAN: Spatial Attention-based Residuals for Facial Expression Manipulation
Third, we proposed to train the complete network with a residual connection which relieves the generator of pressure to generate the input face image thereby producing the desired expression by directly feeding the input image towards the end of the generator.
US-GAN: On the importance of Ultimate Skip Connection for Facial Expression Synthesis
We demonstrate the benefit of using an ultimate skip (US) connection for facial expression synthesis using generative adversarial networks (GAN).
Masked Linear Regression for Learning Local Receptive Fields for Facial Expression Synthesis
Compared to facial expression recognition, expression synthesis requires a very high-dimensional mapping.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Pixel-based Facial Expression Synthesis
The quality of GAN results significantly degrades when testing images are from a slightly different distribution.
