#Image Animation

The project demonstrates a neural network application that animates anime-style characters from single images, featuring a manual poser and a puppeteer tool. It supports interaction via sliders and real-time webcam input, requiring a modern Nvidia GPU. Test it easily on Google Colab without the need for local installations. Necessary dependencies are Python 3.6+, PyTorch, and OpenCV. Images should adhere to specific size and format guidelines for compatibility, offering extensive user engagement options for dynamic animation creation.

MOFA-Video facilitates image animation by leveraging sparse-to-dense motion generation and flow-based adaptation within a Video Diffusion Model. It allows animation of static images using diverse control signals, including trajectories and keypoint sequences. Developed by Tencent AI Lab and the University of Tokyo, this technology is presented at ECCV 2024. The project provides both training and inference code, focusing on accessibility through comprehensive guides and demonstrations. Experience the conversion of static imagery to dynamic motion with MOFA-Video.

The project facilitates open-domain image animation using brief user prompts, turning static images into dynamic animations. It presents various transformation examples like 'Tune the head' and 'Flap the wings', appealing to developers and creatives intrigued by new image manipulation techniques. The team is preparing a demo for public access, encouraging engagement. This approach introduces a unique method of image animation, proving beneficial for enhancing visual content. For further information and updates, visit the official project website.

Discover advanced techniques in animating real images through text-guided motion control. This method enables detailed animation of static images using text to manage movement properties. Created by researchers from The University of Hong Kong along with Alibaba Group and Ant Group, this project represents a notable step forward in image processing and animation. The code will soon be accessible for various uses like creative content creation and educational purposes.