Layer-Animate for Transparent Video Generation
Jingqi Bai, Jingkai Zhou, Benzhi Wang, Weihua Chen, Yang Yang, Zhen Lei, Fan Wang
Abstract
Transparent videos with alpha channels play a crucial role in film production, advertising, and augmented reality fields. However, there is currently no available method for producing transparent videos. Traditional methods are time-consuming and labor-intensive, and employing alternative approaches for this task will result in inaccurate transparent regions, constrained motion, and artifacts. To address these challenges, we propose Layer-Animate, the first method capable of generating transparent videos. Our method comprises two stages: in the first stage, transparent images are generated as the base images to provide content and transparency information for the next stage. In the second stage, Inter-Frame Attention is applied to decouple content from motion, enabling the motion module to focus better on action. Layer-Animate is the first method used to generate transparent videos with accurate transparent regions, sufficient motion, and no artifacts, as demonstrated by notable improvements in qualitative and quantitative metrics.
BibTeX
@inproceedings{icassp2025_layeranimatefort,
title = {Layer-Animate for Transparent Video Generation},
author = {Jingqi Bai and Jingkai Zhou and Benzhi Wang and Weihua Chen and Yang Yang and Zhen Lei and Fan Wang},
booktitle = {ICASSP 2025},
year = {2025}
}