YingqingHe
commented
2 years ago Hi. (1) Our method does not need to find the shadow part in the latent space. Instead, we aim to find the latent vector which represent the clean face with no shadow. In order to do this, we propose a 3-stage optimization process to get the latent vector only for the shadow-free face (which details can be found in our paper). (2) In stage1, we create 500 latent vectors only for a better initialization of the latent vector, and we choose a best one which generated image has the lowest perceptural loss with the input image. (3) Actually our method is not based on manipulation in latent space. We explicitly model the shadow generation process via the color matrix and the shadow mask. More details can be checked in our paper. Thanks!
SleyAI
Hello, I'm currently trying to implement the first step of your proposed algorithm (input: portrait image, face mask, output: shadow free image). I successfully created the face mask with the Bisenet and removed the background from the portrait image. In the next step I received the latent vectors from StyleGAN.
My question now is: How do you explore the latent space to find the relevant parts of the vector which control the shadows? You create K random latent vectors but what is your strategy? How many values do you manipulate in every sample? Any hint would be very helpful to me! Thanks in advance.