Controllable Editing

Controllable image and 3D model editing aims to modify visual content precisely based on user instructions, transcending simple transformations. Current research heavily utilizes diffusion models, often coupled with large language models (LLMs) or other modalities like masks and point-based interactions, to achieve fine-grained control over edits. These advancements are improving the efficiency and realism of image and 3D asset manipulation, impacting fields like digital art, content creation, and data augmentation for computer vision tasks. The focus is on enhancing both the precision and flexibility of editing, addressing challenges such as preserving original image structure and handling complex, multi-modal instructions.