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

Jamie Wynn, Zawar Qureshi, Jakub Powierza, Jamie Watson, Mohamed Sayed

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 multiview 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 depthguided 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.