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新的AllocEmbed框架通过自适应帧预算优化视频检索

提出了一种名为AllocEmbed的新框架,通过自适应地为更多帧分配视觉输入预算来改进视频检索系统。该方法使用一个轻量级分配器,根据低成本预览为帧分配分辨率,在保留重要帧细节的同时降低其他部分的成本。该框架与现有检索系统集成,无需更改嵌入模型或下游管道,实验表明其检索性能优于预算匹配方法。 AI

影响 这项研究通过优化视觉信息的处理方式,有望带来更高效、更有效的视频检索系统。

排序理由 关于视频嵌入新方法的学术论文。[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 →

新的AllocEmbed框架通过自适应帧预算优化视频检索

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21 / 100
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Tool
关于视频嵌入新方法的学术论文。[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) · Song Jin, Zhongtao Jiang, Chenglei Shen, Huanxuan Liao, Haozhe Chi, Zhiwei Wang, Kun Xu, Yong Liu ·

    嵌入前分配:视频嵌入的自适应视觉输入分配

    arXiv:2609.01778v1 Announce Type: new Abstract: Large-scale video retrieval requires embedding models to encode long and diverse videos under tight visual-input and inference budgets. Existing methods typically sample a small, fixed set of frames at their original resolution, lim…