DReSG: Diffusion Residuals for Stylized Gaussian Splatting

1School of Software Engineering, East China Normal University, Shanghai, China
2School of Computer Science and Technology, East China Normal University, Shanghai, China
3School of Intelligent Interaction, East China Normal University, Shanghai, China

Corresponding author

Pacific Graphics 2026

Teaser

Abstract

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.

Pipeline

Qualitative Results

Attention and Residual Strength

3D-Grounded Feedback

Residual Target Construction

User Study

BibTeX

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