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MagicQuill: An Intelligent Interactive Image Editing System

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arxiv 2411.09703 v2 pith:MFIXVGXO submitted 2024-11-14 cs.CV

classification cs.CV
keywords editingimagesystemmagicquillpreciseachievingactualizationallowing
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 1 Pith paper

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    TalkFashion, a text-driven virtual try-on assistant, reports better semantic consistency and visual quality than four baselines on VITON-HD by combining an LLM router, catalog matching, and automatic mask generation.

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