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Cover image for AI Video Generation Breakthrough: Draw Paths to Control How Objects Move in Generated Videos
Mike Young
Mike Young

Posted on • Originally published at aimodels.fyi

AI Video Generation Breakthrough: Draw Paths to Control How Objects Move in Generated Videos

This is a Plain English Papers summary of a research paper called AI Video Generation Breakthrough: Draw Paths to Control How Objects Move in Generated Videos. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

  • MagicMotion lets users control video generation with trajectory guidance
  • Introduces dense-to-sparse trajectory conditioning strategy
  • Works with any diffusion model without retraining
  • Addresses problems of previous methods that relied on sparse control points
  • Uses RAFT optical flow estimation and PnP sampling
  • Achieves state-of-the-art results in motion controllability

Plain English Explanation

When you watch videos created by AI, you might notice they often look strange - objects move oddly or unrealistically. MagicMotion solves this problem by giving you better control over how things move in AI-generated videos.

Imagine trying to describe how a basketball should b...

Click here to read the full summary of this paper

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