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English(EN) DiCE-CIR: Direct Composition Learning for Efficient Zero-Shot Composed Image Retrieval

DiCE-CIR 引入直接组合学习以实现高效零样本图像检索

研究人员推出了一种新颖的直接组合学习方法 DiCE-CIR,用于高效的零样本组合图像检索。该方法通过直接将参考图像与编辑文本组合,绕过了先前方法中复杂的投影和重新编码步骤。DiCE-CIR 利用大型语言模型从图像-标题对自动生成训练样本,从而无需手动标注即可实现可扩展的训练。该方法在 CIRCO 基准测试中展示了最先进的性能,并在 CIRR 上取得了有竞争力的结果,同时保持了高计算效率。 AI

影响 该方法可以提高依赖多模态查询的图像检索系统的效率和准确性。

排序理由 该集群描述了一篇详细介绍新颖图像检索方法的最新研究论文。

在 Hugging Face Daily Papers 阅读 →

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DiCE-CIR 引入直接组合学习以实现高效零样本图像检索

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该集群描述了一篇详细介绍新颖图像检索方法的最新研究论文。
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报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    DiCE-CIR:用于高效零样本组合图像检索的直接组合学习

    Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text describing the desired modification. Recent ZS-CIR studies have relied on projection-based methods that map a reference image into …

  2. arXiv cs.CV TIER_1 English(EN) · Gwang-Ho Na, Ho-Joong Kim, Seong-Whan Lee ·

    DiCE-CIR:直接组合学习实现高效的零样本组合图像检索

    arXiv:2607.04665v1 Announce Type: new Abstract: Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text describing the desired modification. Recent ZS-CIR studies have relied on projectio…