FateZero: Fusing Attentions for Zero-shot Text-based Video Editing

Understand

The diffusion-based generative models have achieved remarkable success in text-based image generation.

• However, since it contains enormous randomness in generation progress, it is still challenging to apply such models for real-world visual content editing, especially in videos.
• In this paper, we propose FateZero, a zero-shot text-based editing method on real-world videos without per-prompt training or use-specific mask.
• To edit videos consistently, we propose several techniques based on the pre-trained models.