Papers › MagicQuill: An Intelligent Interactive Image Editing System

MagicQuill: An Intelligent Interactive Image Editing System

14 Nov 2024CVPR 2025 1arXiv:2411.09703archive 2025-07-28

Zichen Liu, Yue Yu, Hao Ouyang, Qiuyu Wang, Ka Leong Cheng, Wen Wang, Zhiheng Liu, Qifeng Chen, 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.

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ant-research/MagicQuill officialmentioned on GitHubpytorchNOASSERTION report

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brushnet_blocks ant-research/MagicQuill/MagicQuill/brushnet_nodes.py official repository unverified licence not identified · pointer only · 303ce59710d3f99e · report
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sdxl_pooled ant-research/MagicQuill/MagicQuill/comfy/model_base.py official repository unverified licence not identified · pointer only · afea5a7f0f1406bb · report
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Language ModelingLanguage ModellingLarge Language ModelMultimodal Large Language Model

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