As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

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 …

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 …

We present a novel high-resolution face swapping method using the inherent prior
knowledge of a pre-trained GAN model. Although previous research can leverage …

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 …

The ability of Generative Adversarial Networks to encode rich semantics within their latent
space has been widely adopted for facial image editing. However, replicating their success …

Existing GAN inversion and editing methods work well for aligned objects with a clean
background, such as portraits and animal faces, but often struggle for more difficult …

Point-based interactive editing serves as an essential tool to complement the controllability
of existing generative models. A concurrent work DragDiffusion updates the diffusion latent …

We present a new encoder architecture for the inversion of Generative Adversarial Networks
(GAN). The task is to reconstruct a real image from the latent space of a pre-trained GAN …

Despite the demonstrated editing capacity in the latent space of a pretrained GAN model,
inverting real-world images is stuck in a dilemma that the reconstruction cannot be faithful to …