Stars
[Siggraph Asia 2024] Follow-Your-Emoji: This repo is the official implementation of "Follow-Your-Emoji: Fine-Controllable and Expressive Freestyle Portrait Animation"
[ECCV 2024 Oral] MotionDirector: Motion Customization of Text-to-Video Diffusion Models.
EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditioning
Bring portraits to life in Real Time！onnx/tensorrt support！实时肖像驱动！
High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image Animation
📺 An End-to-End Solution for High-Resolution and Long Video Generation Based on Transformer Diffusion
Code for ICML2020 paper - CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
[ACM MM 2024] This is the official code for "AniTalker: Animate Vivid and Diverse Talking Faces through Identity-Decoupled Facial Motion Encoding"
Official PyTorch implementation for the paper Generalizable Face Landmarking Guided by Conditional Face Warping (CVPR 2024).
Fast and memory-efficient exact attention
This is the official source for our ICCV 2023 paper "EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation"
The official PyTorch implementation of the paper "Human Motion Diffusion Model"
Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024
[CVPR 2024] Make-Your-Anchor: A Diffusion-based 2D Avatar Generation Framework.
Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance
Implementation of MagViT2 Tokenizer in Pytorch
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
Character Animation (AnimateAnyone, Face Reenactment)
[CVPR 2024] MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model
[CSUR] A Survey on Video Diffusion Models
Official implementation of CVPR 2024 paper: "FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any Condition"
My implementation of Few-Shot Adversarial Learning of Realistic Neural Talking Head Models (Egor Zakharov et al.).