Landmark Assisted CycleGAN for Cartoon Face Generation

3. Our Method 3.1. Review of CycleGAN 给定来自两个domain的unpaired training samples x∈X,y∈Yx\in X, y\in Yx∈X,y∈Y,对于其从XXX到YYY的mapping GX→YG_{X\rightarrow Y}GX→Y​,及其判别器DYD_YDY​,adversarial loss定义如下 LGAN(GX→Y,DY)=Ey[log⁡Dy(y)]+Ex[log⁡(1−DY(GX→Y(x)))](1) \begin{aligned} \mathcal{L}_{GAN}&\left ( G_{X\rightarro