Enhancing Stability and Quality in Diffusion-Based Drag Editing

The core message of this work is to introduce GoodDrag, a novel approach that enhances the stability and quality of drag editing using diffusion models. The proposed method addresses the key challenges in existing diffusion-based drag editing techniques through two key contributions: Alternating Drag and Denoising (AlDD) framework and Information-Preserving Motion Supervision.