发表机构
Amazon（亚马逊）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对珠宝虚拟试戴的尺度难题，提出无掩模扩散框架JewelTry及基准JVTO-Bench，通过尺度适配器和注意力机制实现尺度感知，兼顾视觉保真与一致性。
AI 中文摘要
虚拟试戴（VTON）使顾客能够可视化穿戴时尚产品时的效果，并已成为在线购物的重要技术。尽管最近的进展大幅改善了服装虚拟试戴，但珠宝由于其尺寸小、结构刚性以及对细粒度视觉细节的敏感性，仍然是一个具有挑战性且未被充分探索的类别。逼真的珠宝虚拟试戴不仅需要忠实的外观迁移，还需要相对于佩戴者的准确尺度和放置位置。现有的珠宝虚拟试戴方法通常依赖掩模引导，而无掩模方法缺乏对产品尺度建模的显式引导。为弥合这一差距，我们引入了JVTO-Bench，一个用于尺度忠实珠宝虚拟试戴的基准数据集，提供参考源目标三元组，并包含四个主要珠宝类别的真实世界产品尺度标注。基于该基准，我们提出了JewelTry，一个用于尺度感知珠宝虚拟试戴的无掩模扩散框架。JewelTry包含一个尺度适配器，将产品尺寸编码为尺度标记，使模型能够在上下文中学习珠宝物品与周围人体解剖结构之间的尺度关系。为进一步提高珠宝一致性，我们引入了单向条件注意力机制和注意力细化损失，以保留参考珠宝的粗粒度几何和细粒度结构细节。大量实验表明，JewelTry在视觉保真度、背景保留、对象一致性和尺度准确性之间取得了平衡，为无掩模、尺度感知的珠宝虚拟试戴建立了强基线。
英文摘要
Virtual try-on (VTON) enables customers to visualize how fashion products appear when worn and has become an important technology for online shopping. While recent advances have substantially improved garment VTON, jewelry remains a challenging and underexplored category due to its small size, rigid structure, and sensitivity to fine-grained visual details. Realistic jewelry VTON requires not only faithful appearance transfer but also accurate scale and placement relative to the wearer. Existing jewelry VTON methods typically rely on mask guidance, whereas mask-free approaches lack explicit guidance for modeling the product scale. To bridge this gap, we introduce JVTO-Bench, a benchmark dataset for scale-faithful jewelry VTON, providing reference source target triplets with real-world product-scale annotations across four major jewelry categories. Building upon this benchmark, we propose JewelTry, a mask-free diffusion framework for scale-aware jewelry VTON. JewelTry incorporates a scale adapter that encodes product dimensions into a scale token, enabling the model to learn scale relationships between jewelry items and surrounding human anatomy in-context. To further improve jewelry consistency, we introduce a single-directional condition attention mechanism and an attention refinement loss that preserve both coarse geometry and fine-grained structural details of the reference jewelry. Extensive experiments show that JewelTry achieves a balance among visual fidelity, background preservation, object consistency and scale accuracy, establishing a strong baseline for mask-free, scale-aware jewelry virtual try-on.
