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English(EN) SignRR: Retrieve and Refine Real Motion for Sign Language Production

手语生成方法SignRR结合检索与精炼

研究人员开发了一种名为SignRR的新手语生成方法,旨在从口语生成连续的手语动作。该方法结合了真实动作片段的检索和一个使用部分感知残差VQ-VAE的精炼过程。SignRR框架通过保留精细的手部关节细节并解决拼接动作片段时出现的 the inconsistencies,改进了现有方法。在PHOENIX14T和CSL-Daily数据集上的实验表明,SignRR在反向翻译方面取得了最先进的性能,同时保持了具有竞争力的姿态质量。 AI

影响 这种新方法可以提高手语生成系统的准确性和自然度。

排序理由 该集群包含一篇详细介绍新手语生成方法的论文。[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 →

手语生成方法SignRR结合检索与精炼

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该集群包含一篇详细介绍新手语生成方法的论文。[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) · Fidel Omar Tito Cruz, Angie Sanchez Marquina, Summy Farfan, Gissella Bejarano ·

    SignRR:用于手语生成的检索和精炼真实动作

    arXiv:2608.28568v1 Announce Type: new Abstract: Sign language production (SLP) aims to generate continuous signing motion from spoken language, often through gloss-to-pose generation. Prior work mainly follows two paradigms. Generative models synthesize motion from a learned prio…