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DiffGI: Differentiable Geometry Images for High-Fidelity Thin-Shell 3D Generation

11 upvotes · 15 JUL 2026 · Eungjune Shim, Hansol Lee, Eunjung Ju

This paper develops a new method for generating high-fidelity 3D images of thin-shell objects, like garments, by learning a continuous surface representation. Practitioners caring about 3D generation and object modeling might care about this approach because it achieves better results with fewer computational resources.

3D-to-2D mappinggeometry imagescontinuous signed distance functionsdifferentiable Marching Squareslatent diffusion modelstransformer-based models