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English(EN) PoseDreamer: Scalable and Photorealistic Human Data Generation Pipeline with Diffusion Models

PoseDreamer管线使用扩散模型生成合成3D人体数据

研究人员开发了PoseDreamer,一种使用扩散模型生成大规模3D人体网格估计合成数据集的新颖管线。该方法通过生成超过50万个具有精确3D标注的高质量样本,解决了现有真实和合成数据集的局限性。在PoseDreamer数据上训练的模型表现与在传统数据集上训练的模型相当或更优,并且将其与其他数据集结合使用可获得更优异的结果。 AI

影响 该方法可以显著降低创建3D人体姿态估计数据集的成本并扩大规模,从而加速计算机视觉领域的研究和开发。

排序理由 该集群描述了一篇研究论文,其中详细介绍了一种使用扩散模型生成合成数据的新方法。[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 →

PoseDreamer管线使用扩散模型生成合成3D人体数据

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该集群描述了一篇研究论文,其中详细介绍了一种使用扩散模型生成合成数据的新方法。[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) · Lorenza Prospero, Orest Kupyn, Ostap Viniavskyi, Jo\~ao F. Henriques, Christian Rupprecht ·

    PoseDreamer:使用扩散模型实现可扩展、照片级逼真的人体数据生成管线

    arXiv:2603.28763v2 Announce Type: replace Abstract: Acquiring labeled datasets for 3D human mesh estimation is challenging due to depth ambiguities and the inherent difficulty of annotating 3D geometry from monocular images. Existing datasets are either real, with manually annota…