AI RESEARCH
PoreDiT: A Scalable Generative Model for Large-Scale Digital Rock Reconstruction
arXiv CS.AI
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ArXi:2604.10171v1 Announce Type: new This manuscript presents PoreDiT, a novel generative model designed for high-efficiency digital rock reconstruction at gigavoxel scales. Addressing the significant challenges in digital rock physics (DRP), particularly the trade-off between resolution and field-of-view (FOV), and the computational bottlenecks associated with traditional deep learning architectures, PoreDiT leverages a three-dimensional (3D) Swin Transformer to break through these limitations.