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SeamEdit pipeline enables black-box VLM image editing

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced SeamEdit, a novel pipeline designed for semantic editing of large images using Visual-Language Models (VLMs). This training-free, model-agnostic approach treats VLMs as black-box oracles, addressing issues like semantic deformation and visible seams that arise when applying closed-source models to tiled editing. SeamEdit employs a five-stage process, including tile decomposition, VLM inpainting, consistency correction, candidate ranking, and seam fusion, to achieve high-quality edits with natural integration into the surrounding content. AI

IMPACT Enables more sophisticated and seamless semantic editing of large images using existing VLM capabilities.

RANK_REASON The cluster contains a research paper detailing a new method for image editing using VLMs.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

SeamEdit pipeline enables black-box VLM image editing

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The cluster contains a research paper detailing a new method for image editing using VLMs.
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Xiangyu Lyu, Dan Lei ·

    SeamEdit: A Black-Box VLM-Agnostic Pipeline for Large-Image Semantic Editing

    arXiv:2606.13041v1 Announce Type: new Abstract: Semantic region editing for large images must satisfy two requirements at the same time: high generative quality and natural integration with surrounding content. Some related methods rely on white-box models and leave the strong ge…

  2. arXiv cs.CV TIER_1 English(EN) · Dan Lei ·

    SeamEdit: A Black-Box VLM-Agnostic Pipeline for Large-Image Semantic Editing

    Semantic region editing for large images must satisfy two requirements at the same time: high generative quality and natural integration with surrounding content. Some related methods rely on white-box models and leave the strong generation capability of closed-source models unde…

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