Image Morphing

Image morphing aims to seamlessly transition between two images, creating a series of intermediate frames that smoothly blend the source and target. Recent research heavily utilizes diffusion models, often coupled with techniques like latent space interpolation or learned representations (e.g., LoRAs), to achieve high-quality, artifact-free morphing, even across semantically different images. This is further enhanced by incorporating semantic information from large vision models or user sketches to guide the morphing process, addressing limitations of previous methods. Improved image morphing techniques have significant implications for various fields, including animation, special effects, and medical imaging.