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English(EN) ArtSeek: Deep artwork understanding via multimodal in-context reasoning and late interaction retrieval

新ArtSeek框架通过多模态推理增强艺术品理解

研究人员开发了ArtSeek,一个新颖的多模态框架,旨在实现深度艺术品理解。该系统独特之处在于仅依赖图像输入,使其适用于缺乏Wikidata或Wikipedia等外部知识库链接的数字化艺术品。ArtSeek包含一个后期交互多模态检索模块、一个用于预测艺术品属性的对比多任务网络,以及一个由上下文示例驱动的智能体推理策略。该框架利用WikiFragments(一个源自英文维基百科的数据集)来增强知识驱动的多模态推理,并在风格分类和艺术品描述方面展现了最先进的性能。 AI

影响 该框架可以显著提高AI分析和理解数字化艺术品的能力,尤其是在缺乏丰富元数据的藏品中。

排序理由 该集群描述了一篇详细介绍新颖艺术品分析框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新ArtSeek框架通过多模态推理增强艺术品理解

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该集群描述了一篇详细介绍新颖艺术品分析框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Nicola Fanelli, Gennaro Vessio, Giovanna Castellano ·

    ArtSeek:通过多模态上下文推理和后期交互检索实现深度艺术品理解

    arXiv:2507.21917v2 Announce Type: replace Abstract: Analyzing digitized artworks requires both visual interpretation and deep artistic, contextual, and historical knowledge. We introduce ArtSeek, a multimodal framework for art analysis that combines multimodal large language mode…