Appearance Transfer

Appearance transfer aims to modify the visual style of an image while preserving its underlying structure, effectively "painting" one image with the appearance of another. Recent research focuses on leveraging diffusion models and Vision Transformers (ViTs), employing techniques like feature splicing and semantic correspondence mapping to achieve accurate and efficient transfer, even handling complex scenarios with non-rigid transformations. These advancements improve image editing capabilities and have implications for various applications, including image synthesis, style transfer, and content creation tools.