mlsanityData to 14 Oct 2026

StyleMesh: Style Transfer for Indoor 3D Scene Reconstructions

arXiv 2112.01530 ↗First posted 2 Dec 2021cs.CVcited by 58

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Abstract (arXiv)

We apply style transfer on mesh reconstructions of indoor scenes. This enables VR applications like experiencing 3D environments painted in the style of a favorite artist. Style transfer typically operates on 2D images, making stylization of a mesh challenging. When optimized over a variety of poses, stylization patterns become stretched out and inconsistent in size. On the other hand, model-based 3D style transfer methods exist that allow stylization from a sparse set of images, but they require a network at inference time. To this end, we optimize an explicit texture for the reconstructed mesh of a scene and stylize it jointly from all available input images. Our depth- and angle-aware optimization leverages surface normal and depth data of the underlying mesh to create a uniform and consistent stylization for the whole scene. Our experiments show that our method creates sharp and detailed results for the complete scene without view-dependent artifacts. Through extensive ablation studies, we show that the proposed 3D awareness enables style transfer to be applied to the 3D domain of a mesh. Our method can be used to render a stylized mesh in real-time with traditional rendering pipelines.

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). Builds on 37 of its 62 references that are in the map. First posted on arXiv 2 Dec 2021.

Builds on

37 of 62 references.

References · 37

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  3. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,117
  4. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,694
  5. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 2,010
  6. 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,376
  7. 2017Understanding the Effective Receptive Field in Deep Convolutional Neural Networkscited by 553
  8. 2017Neural 3D Mesh Renderercited by 437
  9. 2021Advances in Neural Renderingcited by 365
  10. 2019Deferred Neural Rendering: Image Synthesis using Neural Texturescited by 253
  11. 2019Texture Fields: Learning Texture Representations in Function Spacecited by 210
  12. 2021Point-Based Neural Rendering with Per-View Optimizationcited by 190
25 more
  1. 2016Texture Networks: Feed-forward Synthesis of Textures and Stylized Imagescited by 174
  2. 2019Style Transfer by Relaxed Optimal Transport and Self-Similaritycited by 168
  3. 2018Scan2CAD: Learning CAD Model Alignment in RGB-D Scanscited by 142
  4. 2018The Contextual Loss for Image Transformation with Non-Aligned Datacited by 135
  5. 2016BundleFusion: Real-time Globally Consistent 3D Reconstruction using On-the-fly Surface Re-integrationcited by 116
  6. 2017ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scanscited by 103
  7. 2021Stylizing 3D Scene via Implicit Representation and HyperNetworkcited by 103
  8. 2016Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesiscited by 102
  9. 2016Controlling Perceptual Factors in Neural Style Transfercited by 100
  10. 2017Coherent Online Video Style Transfercited by 96
  11. 2020Arbitrary Video Style Transfer via Multi-Channel Correlationcited by 84
  12. 2019SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scanscited by 77
  13. 2021Learning to Stylize Novel Viewscited by 76
  14. 20213DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variationscited by 58
  15. 2017Artistic style transfer for videos and spherical imagescited by 45
  16. 2020SPSG: Self-Supervised Photometric Scene Generation from RGB-D Scanscited by 34
  17. 2020Optical Flow Distillation: Towards Efficient and Stable Video Style Transfercited by 34
  18. 2017Characterizing and Improving Stability in Neural Style Transfercited by 31
  19. 2020Adversarial Texture Optimization from RGB-D Scanscited by 30
  20. 2018ReCoNet: Real-time Coherent Video Style Transfer Networkcited by 26
  21. 2021In the light of feature distributions: moment matching for Neural Style Transfercited by 26
  22. 2020Real-time Localized Photorealistic Video Style Transfercited by 24
  23. 2021Exemplar-Based 3D Portrait Stylizationcited by 21
  24. 2018StyleBlit: Fast Example-Based Stylization with Local Guidancecited by 10
  25. 2020Geometric Style Transfercited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 9; 2023: 18; 2024: 14; 2025: 9; 2026: 8.

58 papers.

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  1. 2022ARF: Artistic Radiance Fieldscited by 147
  2. 2022NeRF-Art: Text-Driven Neural Radiance Fields Stylizationcited by 126
  3. 2023AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Controlcited by 84
  4. 2023StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fieldscited by 79
  5. 2022Unified Implicit Neural Stylizationcited by 67
  6. 2023RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent Geometry and Texturecited by 53
  7. 2022ArtFID: Quantitative Evaluation of Neural Style Transfercited by 49
  8. 2022UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scenecited by 47
  9. 2023SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priorscited by 43
  10. 20233D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillationcited by 35
  11. 2023AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networkscited by 34
  12. 2022SNeRF: Stylized Neural Implicit Representations for 3D Scenescited by 26
38 more
  1. 2023DreamSpace: Dreaming Your Room Space with Text-Driven Panoramic Texture Propagationcited by 25
  2. 2023Locally Stylized Neural Radiance Fieldscited by 20
  3. 2024Chat-Edit-3D: Interactive 3D Scene Editing via Text Promptscited by 19
  4. 2023Text2Scene: Text-driven Indoor Scene Stylization with Part-aware Detailscited by 18
  5. 2024Geometry Transfer for Stylizing Radiance Fieldscited by 16
  6. 2024Gaussian Splatting in Stylecited by 16
  7. 2023Free-Editor: Zero-shot Text-driven 3D Scene Editingcited by 14
  8. 2024StyleTex: Style Image-Guided Texture Generation for 3D Modelscited by 14
  9. 2024Reference-based Controllable Scene Stylization with Gaussian Splattingcited by 12
  10. 2023Editing 3D Scenes via Text Prompts without Retrainingcited by 8
  11. 2022Language-guided Semantic Style Transfer of 3D Indoor Scenescited by 7
  12. 2025ABC-GS: Alignment-Based Controllable Style Transfer for 3D Gaussian Splattingcited by 7
  13. 2023Instruct-Video2Avatar: Video-to-Avatar Generation with Instructionscited by 6
  14. 2023ARF-Plus: Controlling Perceptual Factors in Artistic Radiance Fields for 3D Scene Stylizationcited by 6
  15. 2024G-Style: Stylized Gaussian Splattingcited by 5
  16. 2025Balanced Image Stylization with Style Matching Scorecited by 5
  17. 2026PEGAsus: 3D Personalization of Geometry and Appearancecited by 5
  18. 2023AlteredAvatar: Stylizing Dynamic 3D Avatars with Fast Style Adaptationcited by 4
  19. 20243DStyleGLIP: Part-Tailored Text-Guided 3D Neural Stylizationcited by 4
  20. 2025Styl3R: Instant 3D Stylized Reconstruction for Arbitrary Scenes and Stylescited by 4
  21. 2025Multi-StyleGS: Stylizing Gaussian Splatting with Multiple Stylescited by 4
  22. 2023Instant Photorealistic Neural Radiance Fields Stylizationcited by 3
  23. 2023S2RF: Semantically Stylized Radiance Fieldscited by 3
  24. 2023MuVieCAST: Multi-View Consistent Artistic Style Transfercited by 3
  25. 2024S-DyRF: Reference-Based Stylized Radiance Fields for Dynamic Scenescited by 3
  26. 2025GT2-GS: Geometry-aware Texture Transfer for Gaussian Splattingcited by 3
  27. 20253D PixBrush: Image-Guided Local Texture Synthesiscited by 3
  28. 2025Stylos: Multi-View 3D Stylization with Single-Forward Gaussian Splattingcited by 3
  29. 2022LISA: Localized Image Stylization with Audio via Implicit Neural Representationcited by 2
  30. 2024StyleDyRF: Zero-shot 4D Style Transfer for Dynamic Neural Radiance Fieldscited by 2
  31. 2024MeshBrush: Painting the Anatomical Mesh with Neural Stylization for Endoscopycited by 2
  32. 2024StyleCity: Large-Scale 3D Urban Scenes Stylizationcited by 2
  33. 2026Rollback-Free Stable Brick Structures Generationcited by 2
  34. 2024Style-Consistent 3D Indoor Scene Synthesis with Decoupled Objectscited by 1
  35. 2024G3DST: Generalizing 3D Style Transfer with Neural Radiance Fields across Scenes and Stylescited by 1
  36. 2026Chat-Edit-3D++: Interactive 3D and 4D Scene Editing via Large Language Modelscited by 1
  37. 2022Take One Gram of Neural Features, Get Enhanced Group Robustnesscited by 0
  38. 2023ZIGNeRF: Zero-shot 3D Scene Representation with Invertible Generative Neural Radiance Fieldscited by 0

50 most cited of 58 All 58 (JSON)