Image Colorization on CelebA-HQ Dataset

This project focuses on Image Colorization for human face images, primarily using a U-Net architecture, while also exploring the use of PatchGAN to potentially enhance the realism and overall visual quality of the generated colorized images.

Experiments

Model	Loss Function	PSNR $\uparrow$	SSIM $\uparrow$
U-Net	$\alpha \mathcal{L_2}$ + $\beta \mathcal{L_{percept}}$	25.4007	0.954
U-Net + PatchGAN	$\alpha \mathcal{L_2}$ + $\beta \mathcal{L_{percept}}$ + $\theta \mathcal{L_{adv}} $	24.7444	0.9405
U-Net + PatchGAN	$\alpha \mathcal{L_1}$ + $\beta \mathcal{L_{percept}}$ + $\theta \mathcal{L_{adv}} $	24.9338	0.9454
U-Net + PatchGAN	$\alpha \mathcal{L_1}$ + $\theta \mathcal{L_{adv}} $	updating	updating