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English(EN) Delta-Adapter: Scalable Exemplar-Based Image Editing with Single-Pair Supervision

Delta-Adapter 支持单对监督图像编辑

研究人员开发了 Delta-Adapter,一种新颖的图像编辑方法,仅需要一个源目标图像对进行监督,无需多对图像或文本指导。该方法使用预训练的视觉编码器从示例对中提取“语义差值”,并通过适配器将其注入编辑模型。该技术允许更具可扩展性的训练数据整理,并提高对各种编辑任务的泛化能力,在准确性和一致性方面优于现有方法。 AI

影响 通过减少数据监督要求,实现更具可扩展性和泛化能力的图像编辑模型。

排序理由 介绍图像编辑新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Delta-Adapter 支持单对监督图像编辑

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介绍图像编辑新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xudong Mao ·

    Delta-Adapter:基于单对监督的可扩展示例式图像编辑

    Exemplar-based image editing applies a transformation defined by a source-target image pair to a new query image. Existing methods rely on a pair-of-pairs supervision paradigm, requiring two image pairs sharing the same edit semantics to learn the target transformation. This cons…