mlsanityData to 7 Oct 2026

Optimization-Free Style Transfer for 3D Gaussian Splats

arXiv 2508.05813 ↗First posted 7 Aug 2025cs.CVcited by 0

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Abstract (arXiv)

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, allowing for direct stylization on a .ply or .splat file without requiring the original camera views. 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 also allows for fast stylization of splats with no additional training, achieving speeds under 2 minutes even on CPU-based consumer 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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 42 of its 58 references that are in the map. First posted on arXiv 7 Aug 2025.

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References · 42

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  3. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
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  6. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
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  11. 2023LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPScited by 420
  12. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 401
30 more
  1. 2023Compact 3D Gaussian Representation for Radiance Fieldcited by 365
  2. 2017Universal Style Transfer via Feature Transformscited by 352
  3. 2022Inversion-Based Style Transfer with Diffusion Modelscited by 290
  4. 2023Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesiscited by 232
  5. 2023Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfercited by 194
  6. 2023COLMAP-Free 3D Gaussian Splattingcited by 193
  7. 2021StyTr2: Image Style Transfer with Transformerscited by 186
  8. 2022ARF: Artistic Radiance Fieldscited by 147
  9. 2023Compact 3D Scene Representation via Self-Organizing Gaussian Gridscited by 147
  10. 2022VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Gridscited by 133
  11. 2023CompGS: Smaller and Faster Gaussian Splatting with Vector Quantizationcited by 127
  12. 2021Stylizing 3D Scene via Implicit Representation and HyperNetworkcited by 103
  13. 2016Controlling Perceptual Factors in Neural Style Transfercited by 99
  14. 2023StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fieldscited by 79
  15. 2024StyleGaussian: Instant 3D Style Transfer with Gaussian Splattingcited by 78
  16. 2024StyleMaster: Stylize Your Video with Artistic Generation and Translationcited by 47
  17. 2017Artistic style transfer for videos and spherical imagescited by 45
  18. 2024GSEdit: Efficient Text-Guided Editing of 3D Objects via Gaussian Splattingcited by 36
  19. 2024SGSST: Scaling Gaussian Splatting StyleTransfercited by 20
  20. 2024StyleSplat: 3D Object Style Transfer with Gaussian Splattingcited by 18
  21. 2024Gaussian Splatting in Stylecited by 16
  22. 2020Lagrangian Neural Style Transfer for Fluidscited by 11
  23. 2024ICE-G: Image Conditional Editing of 3D Gaussian Splatscited by 11
  24. 2018StyleBlit: Fast Example-Based Stylization with Local Guidancecited by 10
  25. 2024G-Style: Stylized Gaussian Splattingcited by 5
  26. 2024Low Latency Point Cloud Rendering with Learned Splattingcited by 5
  27. 2020Style Transfer for Light Field Photographycited by 3
  28. 2022SelectionConv: Convolutional Neural Networks for Non-rectilinear Image Datacited by 3
  29. 2024Surface-aware Mesh Texture Synthesis with Pre-trained 2D CNNscited by 3
  30. 2022Interpolated SelectionConv for Spherical Images and Surfacescited by 2

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