Morpheus: Text-Driven 3D Gaussian Splat Shape and Color Stylization

Jamie Wynn, Z. Qureshi, Jakub Powierza, Jamie Watson, Mohamed Sayed
2/10/2026

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Abstract

Exploring real-world spaces using novel-view synthesis is fun, and reimagining those worlds in a different style adds another layer of excitement. Stylized worlds can also be used for downstream tasks where there is limited training data and a need to expand a model’s training distribution. Most current novel-view synthesis stylization techniques lack the ability to convincingly change geometry. This is because editing geometry while maintaining multi-view consistency is very challenging. In this work, we propose a new autoregressive 3D Gaussian Splatting stylization method. As part of this method, we contribute a new RGBD diffusion model that allows for strength control over appearance and shape stylization. To ensure consistency across stylized frames, we use a combination of novel depth-guided cross attention, feature injection, and a ControlNet conditioned on composite frames for guiding the stylization of new frames. We validate our method via extensive qualitative results, quantitative experiments, and a user study.

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Cite this paper

@article{wynn2026morpheus,
  title  = {Morpheus: Text-Driven 3D Gaussian Splat Shape and Color Stylization},
  author = {Jamie Wynn and Z. Qureshi and Jakub Powierza and Jamie Watson and Mohamed Sayed},
  year   = {2026},
  eprint = {2503.02009},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2503.02009},
  journal = {CVPR 2025 2025}
}

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