Cage-based Texture Transfer with Geometric Filtering

June 23, 2026 ยท Grace Period ยท ๐Ÿ› SIGGRAPH 2026

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Authors Rose Mei Zhou, Lynnette Hui Xian Ng, Adrian Xuan Wei Lim, Conor Griffin, Faraz Baghernezhad arXiv ID 2606.25220 Category cs.CV: Computer Vision Cross-listed cs.GR Citations 0 Venue SIGGRAPH 2026
Abstract
Real-time texture transfer expands the creative horizon for interactive applications, enabling seamless detail projection in scenarios that range from digital character cosmetics to procedural automotive texturing. Yet, its practical application is governed by inherent trade-offs between processing speed and suppression of artifacts. Low-latency transfer methods frequently fail to suppress artifacts, and robust alternatives rely on large-scale models that are costly in training and memory. Our proposed method bridges the gap between efficiency and robustness by using a cage-based geometric filtering method to identify Non-Cosmetic Zones (NCZs) for artifact suppression. While other models are resource-intensive and require multiple days of training on manually annotated datasets, we are able to successfully suppress artifacts and achieve immediate deployment on consumer-grade hardware. Our framework achieved highly efficient runtimes of ~70ms on mobile devices for a ~4.8k triangle mesh.
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