Abstract
The success of 3DGS in generative and editing applications has sparked growing interest in 3DGS-based style transfer. However, current methods still face two major challenges: (1) multi-view inconsistency often leads to style conflicts, resulting in appearance smoothing and distortion; and (2) heavy reliance on VGG features, which struggle to disentangle style and content from style images, often causing content leakage and excessive stylization. To tackle these issues, we introduce \textbf{FantasyStyle}, a 3DGS-based style transfer framework, and the first to rely entirely on diffusion model distillation. It comprises two key components: (1) \textbf{Multi-View Frequency Consistency}. We enhance cross-view consistency by applying a 3D filter to multi-view noisy latent, selectively reducing low-frequency components to mitigate stylized prior conflicts. (2) \textbf{Controllable Stylized Distillation}. To suppress content leakage from style images, we introduce negative guidance to exclude undesired content. In addition, we identify the limitations of Score Distillation Sampling and Delta Denoising Score in 3D style transfer and remove the reconstruction term accordingly. Building on these insights, we propose a controllable stylized distillation that leverages negative guidance to more effectively optimize the 3D Gaussians. Extensive experiments demonstrate that our method consistently outperforms state-of-the-art approaches, achieving higher stylization quality and visual realism across various scenes and styles.
Abstract (translated)
3DGS在生成和编辑应用中的成功激发了人们对基于3DGS的风格迁移的兴趣日益增长。然而，目前的方法仍然面临两大挑战：（1）多视角不一致性常常导致风格冲突，从而出现外观平滑化和扭曲；（2）过度依赖VGG特征，这使得从风格图像中区分风格和内容变得困难，通常会导致内容泄露和过度风格化。为了解决这些问题，我们引入了**FantasyStyle**，这是一个基于3DGS的风格迁移框架，并且是第一个完全依赖于扩散模型蒸馏的方法。该框架包含两个关键组件： （1）**多视角频率一致性**：通过在多视角噪声潜在变量上应用三维滤波器来增强跨视图的一致性，选择性地减少低频成分以减轻风格化的先验冲突。 （2）**可控的风格化蒸馏**：为了抑制从样式图像中泄露内容的问题，我们引入了负向指导来排除不需要的内容。此外，我们还指出了3D风格迁移中评分蒸馏采样和Delta去噪评分的局限性，并相应地移除了重构项。基于这些洞察，我们提出了一个可控的风格化蒸馏方法，利用负向指导更有效地优化三维高斯分布。 大量的实验表明，我们的方法在各种场景和风格下始终优于最先进的方法，在风格质量和视觉逼真度方面表现更好。
URL
https://arxiv.org/abs/2508.08136
