Despite recent advances in syncing lip movements with any audio waves, current methods
still struggle to balance generation quality and the model's generalization ability. Previous …

Recent advancements in personalized image generation using diffusion models have been
noteworthy. However existing methods suffer from inefficiencies due to the requirement for …

The great advancements of generative adversarial networks and face recognition models in
computer vision have made it possible to swap identities on images from single sources …

Deepfake is a technology dedicated to creating highly realistic facial images and videos
under specific conditions, which has significant application potential in fields such as …

In this paper, we propose DiffSwap, a diffusion model based framework for high-fidelity and
controllable face swapping. Unlike previous work that relies on carefully designed network …

We present a novel paradigm for high-fidelity face swapping that faithfully preserves the
desired subtle geometry and texture details. We rethink face swapping from the perspective …

Current face reenactment and swapping methods mainly rely on GAN frameworks, but
recent focus has shifted to pre-trained diffusion models for their superior generation …

In human-centric content generation the pre-trained text-to-image models struggle to
produce user-wanted portrait images which retain the identity of individuals while exhibiting …

We propose a novel approach to animate human hair in a still portrait photo. Existing work
has largely studied the animation of fluid elements such as water and fire. However, hair …

The SOTA face swap models still suffer the problem of either target identity (ie, shape) being
leaked or the target non-identity attributes (ie, background, hair) failing to be fully preserved …