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Muyao Niu
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README.md
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MOFA-Video: Controllable Image Animation via Generative Motion
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<a href=''><img src='https://img.shields.io/badge/ArXiv-PDF-red'></a> <a href='https://myniuuu.github.io/MOFA_Video'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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<a href='https://myniuuu.github.io/' target='_blank'>Muyao Niu</a> <sup>1,2</sup>
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We introduce MOFA-Video, a method designed to adapt motions from different domains to the frozen Video Diffusion Model. By employing <u>sparse-to-dense (S2D) motion generation</u> and <u>flow-based motion adaptation</u>, MOFA-Video can effectively animate a single image using various types of control signals, including trajectories, keypoint sequences, AND their combinations.
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<img src="assets/images/pipeline.png">
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<h1>
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MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model
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</h1>
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<a href=''><img src='https://img.shields.io/badge/ArXiv-PDF-red'></a> <a href='https://myniuuu.github.io/MOFA_Video'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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<div>
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<a href='https://myniuuu.github.io/' target='_blank'>Muyao Niu</a> <sup>1,2</sup>
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We introduce MOFA-Video, a method designed to adapt motions from different domains to the frozen Video Diffusion Model. By employing <u>sparse-to-dense (S2D) motion generation</u> and <u>flow-based motion adaptation</u>, MOFA-Video can effectively animate a single image using various types of control signals, including trajectories, keypoint sequences, AND their combinations.
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<p align="center">
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<img src="assets/images/pipeline.png">
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</p>
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