“Enhancing Image Representation in Conditional Image Synthesis”, 2023-02-13 ():
Even though deep neural network-based conditional image synthesis has shown impressive advances in terms of image quality, they still fall short of dealing with domain-dependent global and local styles and distinct shape representations of synthesized images.
To address this issue, we propose a novel GAN-based conditional image synthesis model that incorporates a conditional normalization layer called IAN for style and edge-weighted shape enhancing loss for shape.
Comparative experiments and ablation studies on popular and different domain datasets show that the proposed model outperformed other popular image-to-image translation model for diverse image domains.
[Keywords: generative model, conditional image synthesis, image representation, normalization layer, edge detection]