The Curious Case of End Token: A Zero-Shot Disentangled Image Editing using CLIP

Understand

Diffusion models have become prominent in creating high-quality images.

• However, unlike GAN models celebrated for their ability to edit images in a disentangled manner, diffusion-based text-to-image models struggle to achieve the same level of precise attribute manipulation without compromising image coherence.
• In this paper, CLIP which is often used in popular text-to-image diffusion models such as Stable Diffusion is capable of performing disentangled editing in a zero-shot manner.
• Through both qualitative and quantitative comparisons with state-of-the-art editing methods, we show that our approach yields competitive results.