Snapshot 3D and texture imaging with structured illumination

We demonstrate a snapshot 3D and texture imaging method based on structured illumination. A calibrated projector-camera system is modeled using a differentiable projector-camera image formation model, enabling physics-guided, unsupervised learning to jointly recover 3D surface geometry and RGB reflectance from a single captured image. Experimental results show good agreement with conventional structured-light reconstruction, achieving millimeter-level depth accuracy consistent with triangulation-based resolution analysis. This method offers a promising solution for applications such as autonomous vehicle navigation and industrial metrology.