Bring portraits to life!
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Updated
Jun 14, 2025 - Python
Bring portraits to life!
text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)
🚀 Truly open-source AI avatar(digital human) toolkit for offline video generation and digital human cloning.
HunyuanVideo: A Systematic Framework For Large Video Generation Model
Wan: Open and Advanced Large-Scale Video Generative Models
A curated list of recent diffusion models for video generation, editing, and various other applications.
VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models
[ECCV 2024] Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance
[ICCV 2023 Oral] Text-to-Image Diffusion Models are Zero-Shot Video Generators
MAGI-1: Autoregressive Video Generation at Scale
[ICCV 2025] Official implementations for paper: VACE: All-in-One Video Creation and Editing
InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)
[ICLR 2025] Pyramidal Flow Matching for Efficient Video Generative Modeling
[ECCV 2024, Oral] DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors
MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Visual Conditioned Parallel Denoising
A python tool that uses GPT-4, FFmpeg, and OpenCV to automatically analyze videos, extract the most interesting sections, and crop them for an improved viewing experience.
[ICLR2025, ICML2025, NeurIPS2025 Spotlight] Quantized Attention achieves speedup of 2-5x compared to FlashAttention, without lossing end-to-end metrics across language, image, and video models.
A unified inference and post-training framework for accelerated video generation.
High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
Official implementations for paper: DreamTalk: When Expressive Talking Head Generation Meets Diffusion Probabilistic Models
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