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AnyI2V: Animating Any Conditional Image with Motion Control

Ziye Li, Hao Luo, Xincheng Shuai, Henghui Ding

2025-07-17

AnyI2V: Animating Any Conditional Image with Motion Control

Summary

This paper talks about AnyI2V, a new system that lets users animate any image by controlling how it moves over time, without needing extra training for each new image.

What's the problem?

The problem is that animating images to create videos usually requires training specific models for each type of image or motion, which is slow and limited.

What's the solution?

The authors created AnyI2V, a framework that uses a training-free approach to animate images based on motion paths that users define. It supports different kinds of images and motions, making video generation flexible and easy.

Why it matters?

This matters because it allows anyone to quickly turn still images into animated videos with custom movements, making video creation faster and more accessible for creative projects and applications.

Abstract

AnyI2V is a training-free framework that animates conditional images with user-defined motion trajectories, supporting various data types and enabling flexible video generation.