Audio-Synchronized Visual Animation

Fuente: arXiv
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Hauptverfasser: Zhang, Lin, Mo, Shentong, Zhang, Yijing, Morgado, Pedro
Format: Preprint
Veröffentlicht: 2024
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author Zhang, Lin
Mo, Shentong
Zhang, Yijing
Morgado, Pedro
author_facet Zhang, Lin
Mo, Shentong
Zhang, Yijing
Morgado, Pedro
contents Current visual generation methods can produce high quality videos guided by texts. 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 (ASVA), a task animating a static image to demonstrate motion dynamics, temporally guided by audio clips across multiple classes. To this end, we present AVSync15, a dataset curated from VGGSound with videos featuring synchronized audio visual events across 15 categories. We also present a diffusion model, AVSyncD, capable of generating dynamic animations guided by audios. Extensive evaluations validate AVSync15 as a reliable benchmark for synchronized generation and demonstrate our models superior performance. We further explore AVSyncDs 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. More videos on project webpage https://lzhangbj.github.io/projects/asva/asva.html.
format Preprint
id arxiv_https___arxiv_org_abs_2403_05659
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Audio-Synchronized Visual Animation
Zhang, Lin
Mo, Shentong
Zhang, Yijing
Morgado, Pedro
Computer Vision and Pattern Recognition
Current visual generation methods can produce high quality videos guided by texts. 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 (ASVA), a task animating a static image to demonstrate motion dynamics, temporally guided by audio clips across multiple classes. To this end, we present AVSync15, a dataset curated from VGGSound with videos featuring synchronized audio visual events across 15 categories. We also present a diffusion model, AVSyncD, capable of generating dynamic animations guided by audios. Extensive evaluations validate AVSync15 as a reliable benchmark for synchronized generation and demonstrate our models superior performance. We further explore AVSyncDs 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. More videos on project webpage https://lzhangbj.github.io/projects/asva/asva.html.
title Audio-Synchronized Visual Animation
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2403.05659