Audio-Synchronized Visual Animation

Lin Zhang, Shentong Mo, Yijing Zhang, Pedro Morgado* ;

Abstract


"Current visual generation methods can produce high-quality videos guided by text prompts. However, effectively controlling object dynamics remains a challenge. This work explores audio as a cue to generate temporally synchronized image animations. We introduce Audio-Synchronized Visual Animation (), a task that aims to animate a static image of an object with motions temporally guided by audio clips. To this end, we present , a dataset curated from VGGSound with videos featuring synchronized audio-visual events across 15 categories. We also present a diffusion model, , capable of generating audio-guided animations. Extensive evaluations validate as a reliable benchmark for synchronized generation and demonstrate our model’s superior performance. We further explore ’s potential in a variety of audio-synchronized generation tasks, from generating full videos without a base image to controlling object motions with various sounds. We hope our established benchmark can open new avenues for controllable visual generation."

Related Material


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