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English(EN) Towards Vision-Free CIR: Attribute-Augmented Scoring and LLM-Based Reranking for Zero-Shot Composed Image Retrieval

无视觉CIR框架通过LLM重排增强图像检索

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新颖的无视觉组合图像检索（CIR）框架，这是一项复杂的跨模态任务。该方法利用属性增强混合评分来补偿文本表示中丢失的视觉细节，并采用基于LLM的重排来确保顶级结果之间的语义一致性。在CIRR数据集上的实验表明，与现有的零样本CIR方法相比，性能有了显著提升，R@1得分达到44.04%，提高了8.79%。在FashionIQ上的进一步分析突出了语义推理和细粒度视觉匹配之间的平衡，消融研究证实了两种提出技术都有效。 AI

影响 这项研究推动了复杂图像检索任务的无视觉方法，有潜力提高跨模态AI的能力。

排序理由 该集群包含一篇详细介绍图像检索新方法的学术论文。

在 arXiv cs.CV 阅读 →

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无视觉CIR框架通过LLM重排增强图像检索

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该集群包含一篇详细介绍图像检索新方法的学术论文。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Ryotaro Shimada, Yu-Chieh Lin, Yuji Nozawa, Youyang Ng, Osamu Torii, Yusuke Matsui ·

    迈向无视觉的CIR：属性增强评分与基于LLM的重排用于零样本组合图像检索

    arXiv:2607.12621v1 Announce Type: new Abstract: Recent work has shown that "Vision-Free'' approaches (representing images as text) can be effective for standard image retrieval tasks. However, it remains unclear whether this paradigm can effectively handle a more complex, multimo…

  2. arXiv cs.CV TIER_1 English(EN) · Yusuke Matsui ·

    迈向无视觉的CIR：用于零样本组合图像检索的属性增强评分和基于LLM的重排序

    Recent work has shown that "Vision-Free'' approaches (representing images as text) can be effective for standard image retrieval tasks. However, it remains unclear whether this paradigm can effectively handle a more complex, multimodal task, Composed Image Retrieval (CIR), due to…

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