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arxiv:2409.02634

Loopy: Taming Audio-Driven Portrait Avatar with Long-Term Motion Dependency

Published on Sep 4
· Submitted by akhaliq on Sep 5
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Abstract

With the introduction of diffusion-based video generation techniques, audio-conditioned human video generation has recently achieved significant breakthroughs in both the naturalness of motion and the synthesis of portrait details. Due to the limited control of audio signals in driving human motion, existing methods often add auxiliary spatial signals to stabilize movements, which may compromise the naturalness and freedom of motion. In this paper, we propose an end-to-end audio-only conditioned video diffusion model named Loopy. Specifically, we designed an inter- and intra-clip temporal module and an audio-to-latents module, enabling the model to leverage long-term motion information from the data to learn natural motion patterns and improving audio-portrait movement correlation. This method removes the need for manually specified spatial motion templates used in existing methods to constrain motion during inference. Extensive experiments show that Loopy outperforms recent audio-driven portrait diffusion models, delivering more lifelike and high-quality results across various scenarios.

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Incredible work 🚀 That is a real step forward!

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hola compañeros! estamos evolucionando mucho en la inteligancia artificial, ya mismo podremos hacer deep fakes tan realistas que me da miedo el asunto

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good, but how to get access to the model??

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you dont, they didnt release it for ethical reasons which is nonsense.

请问什么时候开源呢?

何时开源!!!!!!!迫不及待!!!!!!!!

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