ZONE: Zero-Shot Instruction-Guided Local Editing

Shanglin Li; Bohan Zeng; Yutang Feng; Sicheng Gao; Xuhui Liu; Jiaming Liu; Li Lin; Xu Tang; Yao Hu; Jianzhuang Liu; Baochang Zhang

arXiv · 2312.16794

ZONE: Zero-Shot Instruction-Guided Local Editing

Shanglin Li·Bohan Zeng·Yutang Feng·Sicheng Gao·Xuhui Liu·Jiaming Liu·Li Lin·Xu Tang·Yao Hu·Jianzhuang Liu·Baochang Zhang

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Abstract

Recent advances in vision-language models like Stable Diffusion have shown remarkable power in creative image synthesis and editing.However, most existing text-to-image editing methods encounter two obstacles: First, the text prompt needs to be carefully crafted to achieve good results, which is not intuitive or user-friendly. Second, they are insensitive to local edits and can irreversibly affect non-edited regions, leaving obvious editing traces. To tackle these problems, we propose a Zero-shot instructiON-guided local image Editing approach, termed ZONE. We first convert the editing intent from the user-provided instruction (e.g., "make his tie blue") into specific image editing regions through InstructPix2Pix. We then propose a Region-IoU scheme for precise image layer extraction from an off-the-shelf segment model. We further develop an edge smoother based on FFT for seamless blending between the layer and the image.Our method allows for arbitrary manipulation of a specific region with a single instruction while preserving the rest. Extensive experiments demonstrate that our ZONE achieves remarkable local editing results and user-friendliness, outperforming state-of-the-art methods. Code is available at https://github.com/lsl001006/ZONE.

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Shanglin Li, Bohan Zeng, Yutang Feng, Sicheng Gao, Xuhui Liu, Jiaming Liu, Li Lin, Xu Tang, Yao Hu, Jianzhuang Liu, Baochang Zhang. 2024-04-12. ZONE: Zero-Shot Instruction-Guided Local Editing. https://arxiv.org/abs/2312.16794

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