Multi-target distortion correction in 3D shape from polarization using a monocular camera system by deep neural networks.

The shape from polarization is a noncontact 3D imaging method that shows great potential, but its application is limited by the monocular camera system and surface integration algorithm. This Letter proposes a novel, to the best of our knowledge, method that employs deep neural networks to enhance multi-target 3D reconstruction, making a significant advancement in the field. By constructing the relationship between targets' blur, distance, and clarity, the proposed method provides accurate spatial information while mitigating inaccuracies arising from the continuous model.