GaussianVTON：基于多阶段高斯泼溅编辑与图像提示的三维人体虚拟试穿
GaussianVTON: 3D Human Virtual Try-ON via Multi-Stage Gaussian Splatting Editing with Image Prompting
AI总结：
GaussianVTON提出一种结合高斯泼溅编辑与二维虚拟试穿的三维试穿流程，首次仅用图像作为编辑提示，通过三阶段细化策略和编辑回忆重建方法，解决面部模糊、服装不准确等问题，实现高质量三维虚拟试穿。
摘要：
电子商务的日益普及凸显了虚拟试穿（VTON）的重要性。然而，以往的研究主要集中在二维领域，并严重依赖大量数据进行训练。三维VTON的研究主要集中于服装与身体形状的兼容性，这一主题在二维VTON中已被广泛探讨。得益于三维场景编辑的进展，二维扩散模型现已通过多视角编辑被适配用于三维编辑。在这项工作中，我们提出了GaussianVTON，一种创新的三维VTON流程，它将高斯泼溅（GS）编辑与二维VTON相结合。为了促进从二维到三维VTON的无缝过渡，我们首次提出仅使用图像作为三维编辑的编辑提示。为进一步解决编辑过程中出现的面部模糊、服装不准确和视角质量下降等问题，我们设计了一个三阶段细化策略，以逐步缓解潜在问题。此外，我们引入了一种新的编辑策略，称为编辑回忆重建（ERR），以解决以往编辑策略在导致复杂几何变化方面的局限性。我们的综合实验证明了GaussianVTON的优越性，为三维VTON提供了新颖视角，同时也为图像提示的三维场景编辑建立了一个新的起点。
英文摘要：
The increasing prominence of e-commerce has underscored the importance of Virtual Try-On (VTON). However, previous studies predominantly focus on the 2D realm and rely heavily on extensive data for training. Research on 3D VTON primarily centers on garment-body shape compatibility, a topic extensively covered in 2D VTON. Thanks to advances in 3D scene editing, a 2D diffusion model has now been adapted for 3D editing via multi-viewpoint editing. In this work, we propose GaussianVTON, an innovative 3D VTON pipeline integrating Gaussian Splatting (GS) editing with 2D VTON. To facilitate a seamless transition from 2D to 3D VTON, we propose, for the first time, the use of only images as editing prompts for 3D editing. To further address issues, e.g., face blurring, garment inaccuracy, and degraded viewpoint quality during editing, we devise a three-stage refinement strategy to gradually mitigate potential issues. Furthermore, we introduce a new editing strategy termed Edit Recall Reconstruction (ERR) to tackle the limitations of previous editing strategies in leading to complex geometric changes. Our comprehensive experiments demonstrate the superiority of GaussianVTON, offering a novel perspective on 3D VTON while also establishing a novel starting point for image-prompting 3D scene editing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
