The incidence field is a learnable monocular 3D prior, determined pixel-wisely by up-to-sacle monocular depthmap and surface normal.With the estimated incidence field, a robust RANSAC algorithm recovers intrinsic.We show the effectiveness of our method through superior performance on synthetic and zero-shot testing datasets.Beyond calibration, we demonstrate downstream applications in image manipulation detection \& restoration, uncalibrated two-view pose estimation, and 3D sensing.

However, the unknown intrinsic parameter hinders their development and deployment.

The incidence field is a learnable monocular 3D prior, determined pixel-wisely by up-to-sacle monocular depthmap and surface normal.With the estimated incidence field, a robust RANSAC algorithm recovers intrinsic.We show the effectiveness of our method through superior performance on synthetic and zero-shot testing datasets.Beyond calibration, we demonstrate downstream applications in image manipulation detection \& restoration, uncalibrated two-view pose estimation, and 3D sensing.