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English(EN) PHA-Net: Prototype-based Hierarchical Alignment Network for Text-Video Retrieval

新的PHA-Net通过原型对齐改进文本-视频检索

研究人员开发了PHA-Net,一种用于文本-视频检索的新型网络,它利用共享原型来有效地对齐跨模态表示。该方法通过增强具有强语义的token并抑制较弱的token来解决文本和视频之间的语义不匹配问题。PHA-Net在多个基准测试中表现出显著的改进,包括MSR-VTT、ActivityNet、VATEX和Charades。 AI

影响 通过改善模态间的语义对齐来增强文本-视频检索能力。

排序理由 该条目是一篇研究论文,详细介绍了用于文本-视频检索的新网络架构,已提交至arXiv。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.IR (Information Retrieval) 阅读 →

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

新的PHA-Net通过原型对齐改进文本-视频检索

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该条目是一篇研究论文,详细介绍了用于文本-视频检索的新网络架构,已提交至arXiv。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Jian Chu ·

    PHA-Net:用于文本-视频检索的原型式分层对齐网络

    With the emergence of large-scale image-text pre-training models, e.g., CLIP, text-video retrieval has experienced substantial advances in recent years. Existing best-performing methods involve aligning cross-modal semantics at individual, local, and global levels simultaneously,…