MagicQuill: An Intelligent Interactive Image Editing System
Authors: name: Zichen Liu, name: Yue Yu, name: Hao Ouyang, name: Qiuyu Wang, name: Ka Leong Cheng, name: Wen Wang, name: Zhiheng Liu, name: Qifeng Chen, name: Yujun Shen

Image editing involves a variety of complex tasks and requires efficient and
precise manipulation techniques. In this paper, we present MagicQuill, an
integrated image editing system that enables swift actualization of creative
ideas. Our system features a streamlined yet functionally robust interface,
allowing for the articulation of editing operations (e.g., inserting elements,
erasing objects, altering color) with minimal input. These interactions are
monitored by a multimodal large language model (MLLM) to anticipate editing
intentions in real time, bypassing the need for explicit prompt entry. Finally,
we apply a powerful diffusion prior, enhanced by a carefully learned two-branch
plug-in module, to process editing requests with precise control. Experimental
results demonstrate the effectiveness of MagicQuill in achieving high-quality
image edits. Please visit https://magic-quill.github.io to try out our system.