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In this work we develop 3D Paintbrush, a technique for automaticallytexturing local semantic regions on meshes via text descriptions. Our method isdesigned to operate directly on meshes, producing texture maps which seamlesslyintegrate into standard graphics pipelines. We opt to simultaneously produce alocalization map (to specify the edit region) and a texture map which conformsto it. This synergistic approach improves the quality of both the localizationand the stylization. To enhance the details and resolution of the texturedarea, we leverage multiple stages of a cascaded diffusion model to superviseour local editing technique with generative priors learned from images atdifferent resolutions. Our technique, referred to as Cascaded ScoreDistillation (CSD), simultaneously distills scores at multiple resolutions in acascaded fashion, enabling control over both the granularity and globalunderstanding of the supervision. We demonstrate the effectiveness of 3DPaintbrush to locally texture a variety of shapes within different semanticregions. Project page: https://threedle.github.io/3d-paintbrush

3D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillation