SadTalker is a generative framework designed to synthesize expressive talking head videos from static portrait images. By mapping audio signals or text prompts to three-dimensional facial motion coefficients, the system synchronizes lip movements, facial expressions, and head orientation to create realistic digital character performances. The project distinguishes itself by decoupling identity from dynamic motion through latent space encoding, ensuring that the generated animations maintain visual fidelity to the source portrait. It supports comprehensive motion synthesis, including full-body
X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attention You Xie , Hongyi Xu , Guoxian Song , Chao Wang , Yichun Shi , Linjie Luo ByteDance Inc.
This repository contains the source code for the CVPR oral paper Animating Arbitrary Objects via Deep Motion Transfer by Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov, Elisa Ricci and Nicu Sebe. We call the proposed deep framework Monkey-Net, as it enables motion transfer by…
Authors official PyTorch implementation of StyleMask: Disentangling the Style Space of StyleGAN2 for Neural Face Reenactment. This paper has been accepted for publication at IEEE Conference on Automatic Face and Gesture Recognition, 2023.
Die Hauptfunktionen von stelabou/stylemask sind: Image Driven Animation.
Open-Source-Alternativen zu stelabou/stylemask sind unter anderem: winfredy/sadtalker — SadTalker is a generative framework designed to synthesize expressive talking head videos from static portrait images.… bytedance/x-portrait — X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attention You Xie , Hongyi Xu , Guoxian Song , Chao… feiiyin/styleheat — paper | project website. gvclab/personalive — Expressive Portrait Image Animation for Live Streaming. harlanhong/cvpr2022-dagan — :fire: If DaGAN is helpful in your photos/projects, please help to :star: it or recommend it to your friends.… aliaksandrsiarohin/monkey-net — This repository contains the source code for the CVPR oral paper Animating Arbitrary Objects via Deep Motion Transfer…