mlsanityData to 7 Oct 2026

DReSG: Diffusion Residuals for Stylized Gaussian Splatting

arXiv 2608.29048 ↗First posted 29 Aug 2026cs.CV cs.GRcited by 0

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

Reference-guided stylization of scenes represented by 3D Gaussian Splatting (3DGS) is important for efficient and controllable 3D content creation. Existing VGG-feature-based 3D stylization methods provide stable rendered-view optimization, but often under-represent expressive reference style cues; diffusion models offer stronger image priors, yet direct per-view or score-based diffusion guidance can lead to view drift, local artifacts, and hard-to-control appearance updates. We present DReSG, a 3D-grounded residual-feedback framework for stylized Gaussian splatting. DReSG represents attention-guided diffusion proposals as residual targets relative to the current render, and progressively absorbs these residuals into a shared Gaussian scene through multi-view Gaussian feedback. To make this feedback stable and controllable, DReSG modulates residual strength during target construction and combines coverage-aware view selection with conflict-filtered color updates during multi-view fitting. Extensive experiments demonstrate that DReSG achieves competitive reference-guided stylization while better preserving scene structure and cross-view stability. Our project page is available at https://vpx-ecnu.github.io/DReSG-website/.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 39 of its 47 references that are in the map. First posted on arXiv 29 Aug 2026.

Builds on

39 of 47 references.

Closest ancestors · 6

Same direction, newest first

  1. 2023GaussianEditor: Editing 3D Gaussians Delicately with Text Instructions27 Nov
  2. 2023MVDream: Multi-view Diffusion for 3D Generation31 Aug
  3. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation25 May
  4. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation1 Dec
  5. 2022Magic3D: High-Resolution Text-to-3D Content Creation18 Nov
  6. 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep

Other references · 33

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  4. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
  5. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  6. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  7. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
  8. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
  9. 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,439
  10. 2020Gradient Surgery for Multi-Task Learningcited by 1,210
  11. 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 482
  12. 2017Universal Style Transfer via Feature Transformscited by 352
21 more
  1. 2022Inversion-Based Style Transfer with Diffusion Modelscited by 290
  2. 2024PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstructioncited by 280
  3. 2024Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Modelscited by 240
  4. 2022ARF: Artistic Radiance Fieldscited by 147
  5. 2022StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learningcited by 140
  6. 2024GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editingcited by 114
  7. 2024DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editingcited by 92
  8. 2023StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fieldscited by 79
  9. 2024StyleGaussian: Instant 3D Style Transfer with Gaussian Splattingcited by 78
  10. 2021Learning to Stylize Novel Viewscited by 76
  11. 2024View-Consistent 3D Editing with Gaussian Splattingcited by 67
  12. 2025FastGS: Training 3D Gaussian Splatting in 100 Secondscited by 39
  13. 2025Attention Distillation: A Unified Approach to Visual Characteristics Transfercited by 32
  14. 2024StylizedGS: Controllable Stylization for 3D Gaussian Splattingcited by 23
  15. 2024SGSST: Scaling Gaussian Splatting StyleTransfercited by 20
  16. 2025Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modelingcited by 18
  17. 2024Style-NeRF2NeRF: 3D Style Transfer From Style-Aligned Multi-View Imagescited by 16
  18. 2025CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splattingcited by 8
  19. 2025ABC-GS: Alignment-Based Controllable Style Transfer for 3D Gaussian Splattingcited by 7
  20. 2023MuVieCAST: Multi-View Consistent Artistic Style Transfercited by 3
  21. 2025GT2-GS: Geometry-aware Texture Transfer for Gaussian Splattingcited by 3

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  1. 2025Morpheus: Text-Driven 3D Gaussian Splat Shape and Color Stylization
  2. 2024GSD: View-Guided Gaussian Splatting Diffusion for 3D Reconstruction
  3. 2025FixingGS: Enhancing 3D Gaussian Splatting via Training-Free Score Distillation
  4. 2026Nix and Fix: Targeting 1000x Compression of 3D Gaussian Splatting with Diffusion Models
  5. 2025ReCoGS: Real-time ReColoring for Gaussian Splatting scenes
  6. 2024DiffGS: Functional Gaussian Splatting Diffusion
  7. 2025Taming Video Diffusion Prior with Scene-Grounding Guidance for 3D Gaussian Splatting from Sparse Inputs
  8. 2025ProSplat: Improved Feed-Forward 3D Gaussian Splatting for Wide-Baseline Sparse Views