Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Chun-Hsiao Yeh, Yilin Wang, Nanxuan Zhao, Richard Zhang, Yuheng Li, Yi Ma, Krishna Kumar Singh
2025-07-08
Summary
This paper talks about X-Planner, a new system that uses a multimodal large language model to understand complex instructions for editing images. It uses a method called chain-of-thought reasoning to break down the instructions step-by-step and create accurate image edits.
What's the problem?
The problem is that most current image editing tools can only handle simple commands and struggle to understand complicated or detailed editing requests, which limits what users can do with AI-based editing.
What's the solution?
The researchers designed X-Planner to connect language understanding with image editing by reasoning through complex instructions in multiple steps. This way, it can follow detailed directions and make precise changes to images, improving the quality and flexibility of AI-driven editing.
Why it matters?
This matters because it allows users to give more natural and complicated instructions to AI for editing images, making digital art, design, and photo editing more powerful and easier to use.
Abstract
X-Planner, a Multimodal Large Language Model-based system, uses chain-of-thought reasoning to interpret complex instructions and generate precise edits, achieving state-of-the-art results in image editing.