mlsanityData to 7 Oct 2026

StyleSplat: 3D Object Style Transfer with Gaussian Splatting

arXiv 2407.09473 ↗First posted 12 Jul 2024cs.CVcited by 18

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Abstract (arXiv)

Recent advancements in radiance fields have opened new avenues for creating high-quality 3D assets and scenes. Style transfer can enhance these 3D assets with diverse artistic styles, transforming creative expression. However, existing techniques are often slow or unable to localize style transfer to specific objects. We introduce StyleSplat, a lightweight method for stylizing 3D objects in scenes represented by 3D Gaussians from reference style images. Our approach first learns a photorealistic representation of the scene using 3D Gaussian splatting while jointly segmenting individual 3D objects. We then use a nearest-neighbor feature matching loss to finetune the Gaussians of the selected objects, aligning their spherical harmonic coefficients with the style image to ensure consistency and visual appeal. StyleSplat allows for quick, customizable style transfer and localized stylization of multiple objects within a scene, each with a different style. We demonstrate its effectiveness across various 3D scenes and styles, showcasing enhanced control and customization in 3D creation.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 28 of its 39 references that are in the map. First posted on arXiv 12 Jul 2024.

Builds on

28 of 39 references.

References · 28

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  2. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
  3. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  4. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  5. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  6. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  7. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  8. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
  9. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  10. 2015A Neural Algorithm of Artistic Stylecited by 480
  11. 2023Gaussian Grouping: Segment and Edit Anything in 3D Scenescited by 387
  12. 2023Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fieldscited by 361
16 more
  1. 2023GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splattingcited by 331
  2. 2019Differentiable Surface Splatting for Point-based Geometry Processingcited by 238
  3. 2023Tracking Anything with Decoupled Video Segmentationcited by 197
  4. 2019Style Transfer by Relaxed Optimal Transport and Self-Similaritycited by 167
  5. 2017Visual Attribute Transfer through Deep Image Analogycited by 123
  6. 2024StyleGaussian: Instant 3D Style Transfer with Gaussian Splattingcited by 78
  7. 2024TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-Promptscited by 76
  8. 2018Arbitrary Style Transfer with Deep Feature Reshufflecited by 75
  9. 2018Stroke Controllable Fast Style Transfer with Adaptive Receptive Fieldscited by 33
  10. 2024StylizedGS: Controllable Stylization for 3D Gaussian Splattingcited by 23
  11. 2024Gaussian Splatting in Stylecited by 16
  12. 2024CoARF: Controllable 3D Artistic Style Transfer for Radiance Fieldscited by 14
  13. 2024ICE-G: Image Conditional Editing of 3D Gaussian Splatscited by 11
  14. 2017Son of Zorn's Lemma: Targeted Style Transfer Using Instance-aware Semantic Segmentationcited by 8
  15. 2019Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentationcited by 7
  16. 2023ARF-Plus: Controlling Perceptual Factors in Artistic Radiance Fields for 3D Scene Stylizationcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 9; 2026: 6.

18 papers.

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  1. 2025A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generationcited by 19
  2. 2025DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interactioncited by 16
  3. 2025TexGS-VolVis: Expressive Scene Editing for Volume Visualization via Textured Gaussian Splattingcited by 9
  4. 2024TRASE: Tracking-free 4D Segmentation and Editingcited by 8
  5. 2025CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splattingcited by 8
  6. 20253DOT: Texture Transfer for 3DGS Objects from a Single Reference Imagecited by 7
  7. 2024ArtNVG: Content-Style Separated Artistic Neighboring-View Gaussian Stylizationcited by 4
  8. 2025FantasyStyle: Controllable Stylized Distillation for 3D Gaussian Splattingcited by 3
  9. 2026Tune-Your-Style: Intensity-tunable 3D Style Transfer with Gaussian Splattingcited by 2
  10. 2024Editing Implicit and Explicit Representations of Radiance Fields: A Surveycited by 1
  11. 2025Mastering Regional 3DGS: Locating, Initializing, and Editing with Diverse 2D Priorscited by 0
  12. 2025Optimization-Free Style Transfer for 3D Gaussian Splatscited by 0
6 more
  1. 2025Image-Conditioned 3D Gaussian Splat Quantizationcited by 0
  2. 2026DiffStyle3D: Consistent 3D Gaussian Stylization via Attention Optimizationcited by 0
  3. 2026Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusioncited by 0
  4. 2026Boosting Zero-Shot 3D Style Transfer with 2D Pre-trained Priorscited by 0
  5. 2026OmniStyle-INR: Universal and Multimodal Style Transfer for INRscited by 0
  6. 2026Owner3D: Ownership-Guided Style Writing for Training-Free Localized 3D Stylizationcited by 0