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English(EN) H-Adapter: Pose-Robust Hairstyle Transfer via Attention-Derived, Source-Aligned Hair Masks

H-Adapter 通过注意力导出的蒙版改进姿态鲁棒的发型迁移

研究人员开发了 H-Adapter,一个旨在提高发型迁移准确性和鲁棒性的新颖系统,尤其是在源图像和参考图像在头部姿态上存在显著差异时。该系统利用区域特定的损失函数来分离头发和非头发元素,从而能够导出源对齐的发型蒙版来指导基于扩散的修复。实验表明,H-Adapter 在姿态变化下的 FID 和 CLIP-I 等指标上取得了优于以往的量化结果,同时还支持文本到图像生成和基于提示的头发颜色控制等扩展功能。 AI

影响 这项研究推进了图像处理领域生成式AI的能力,可能对虚拟试穿应用和创意内容生成产生影响。

排序理由 该集群描述了在 arXiv 学术论文中提出的一种新颖方法。

在 arXiv cs.CV 阅读 →

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H-Adapter 通过注意力导出的蒙版改进姿态鲁棒的发型迁移

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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Seulgi Jeong, Yunseong Cho, Sanghun Park ·

    H-Adapter:通过注意力导出的、源对齐的发型蒙版实现姿态鲁棒的发型迁移

    arXiv:2606.25578v1 Announce Type: new Abstract: Hairstyle transfer has practical applications such as virtual try-on, yet remains challenging when the source and reference exhibit large head-pose discrepancies. We propose H-Adapter, which improves pose robustness by training with…

  2. arXiv cs.CV TIER_1 English(EN) · Sanghun Park ·

    H-Adapter:通过注意力导出的、源对齐的发型掩码实现姿态鲁棒的发型迁移

    Hairstyle transfer has practical applications such as virtual try-on, yet remains challenging when the source and reference exhibit large head-pose discrepancies. We propose H-Adapter, which improves pose robustness by training with a region-specific loss that disentangles hair a…