無需優化的3D高斯濺射風格轉換
Optimization-Free Style Transfer for 3D Gaussian Splats
August 7, 2025
作者: Raphael Du Sablon, David Hart
cs.AI
摘要
針對3D高斯濺射的風格轉換任務,已有許多先前研究進行了探索,但這些方法需要在融入風格資訊或對濺射表示進行特徵提取網絡優化的同時,重建或微調濺射。我們提出了一種無需重建與優化的3D高斯濺射風格化方法。該方法通過在濺射表示的隱式表面上生成圖結構來實現。隨後,採用一種基於表面的前饋風格化技術,並將其插值回場景中的各個濺射。這使得任何風格圖像與3D高斯濺射都能直接使用,無需額外的訓練或優化。此外,該方法還能實現快速的濺射風格化,即使在消費級硬件上也能在2分鐘內完成。我們展示了該方法所達到的質量效果,並與其他3D高斯濺射風格轉換方法進行了比較。相關代碼已公開於https://github.com/davidmhart/FastSplatStyler。
English
The task of style transfer for 3D Gaussian splats has been explored in many
previous works, but these require reconstructing or fine-tuning the splat while
incorporating style information or optimizing a feature extraction network on
the splat representation. We propose a reconstruction- and optimization-free
approach to stylizing 3D Gaussian splats. This is done by generating a graph
structure across the implicit surface of the splat representation. A
feed-forward, surface-based stylization method is then used and interpolated
back to the individual splats in the scene. This allows for any style image and
3D Gaussian splat to be used without any additional training or optimization.
This also allows for fast stylization of splats, achieving speeds under 2
minutes even on consumer-grade hardware. We demonstrate the quality results
this approach achieves and compare to other 3D Gaussian splat style transfer
methods. Code is publicly available at
https://github.com/davidmhart/FastSplatStyler.