sin2pixT
sin2pixT is a deep learning model developed for image-to-image translation tasks. Specifically, it focuses on translating images from a source domain to a target domain, aiming to preserve important content while altering stylistic elements. The model architecture is based on the pix2pix framework, which utilizes a conditional generative adversarial network (cGAN).
The core of sin2pixT lies in its generator and discriminator networks. The generator learns to map an
sin2pixT differs from its predecessor, pix2pix, by incorporating specific architectural modifications or training strategies tailored for