Zero-shot Visual Concept Blending without Text Guidance

Abstract

In this study, we propose a novel image generation technique called “Visual Concept Blending”, which extracts features that are either shared or distinct features from multiple reference images and transfers them to a base image. By using multiple reference images, our method provides fine control over which features are blended into the base image. At the same time, it leverages the CLIP embedding space to facilitate the transfer of higher-level concepts such as shape transformation and motion. The proposed approach directly utilizes existing pre-trained models without requiring additional training, making it both simple and robust. This technique is expected to find wide-ranging applications in fields like art and design.