We look into Generative Adversarial Network (GAN), its prevalent variants and applications
in a number of sectors. GANs combine two neural networks that compete against one …

Generative adversarial networks (GANs) have drawn enormous attention due to their simple
yet effective training mechanism and superior image generation quality. With the ability to …

We present a novel high-fidelity generative adversarial network (GAN) inversion framework
that enables attribute editing with image-specific details well-preserved (eg, background …

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …

Facial editing is an important task in vision and graphics with numerous applications.
However, existing works are incapable to deliver a continuous and fine-grained editing …

We present a framework for training GANs with explicit control over generated facial images.
We are able to control the generated image by settings exact attributes such as age, pose …

Unconditional video generation is a challenging task that involves synthesizing high-quality
videos that are both coherent and of extended duration. To address this challenge …

Image-to-image translation with generative adversarial networks (GANs) has been
extensively studied in recent years. Among the models, StarGAN has achieved image-to …

Intrinsic images, in the original sense, are image-like maps of scene properties like depth,
normal, albedo, or shading. This paper demonstrates that StyleGAN can easily be induced …

Although progress has been made for text-to-image synthesis, previous methods fall short of
generalizing to unseen or underrepresented attribute compositions in the input text. Lacking …