#DynamiCrafter

The DynamiCrafter project employs an innovative approach for animating still images across open domains using text prompts and advanced video diffusion models. The project achieves superior dynamic image generation with high resolutions like 576x1024 and 320x512, ranking highly on the I2V benchmark. Its functionalities include storytelling video creation, frame interpolation, and seamless video looping, with easy-to-access demonstrations available on Hugging Face and Colab. Continuous updates improve dynamic expression and coherence, making it a practical tool for creators.

This project investigates the issue of conditional image leakage in image-to-video diffusion models (I2V-DMs), which causes videos to lack dynamic motion. By proposing practical plug-and-play strategies for both inference and training, the project demonstrates improvements using various I2V-DMs like DynamiCrafter, SVD, and VideoCrafter1. Comprehensive setup instructions and parameter optimization insights make this a key resource for improving video generation.