CVPR 2023 - Inverting the Imaging Process by Learning an Implicit Camera Model

In this episode we discuss Inverting the Imaging Process by Learning an Implicit Camera Model by Xin Huang, Qi Zhang, Ying Feng, Hongdong Li, Qing Wang. The paper introduces a new approach for modeling the physical imaging process of a camera as an implicit neural network, which is able to learn and control camera parameters. This approach is tested on two challenging inverse imaging tasks: all-in-focus and HDR imaging. The results show that the new implicit neural camera model is able to produce visually appealing and accurate images, making it a promising tool for a wide range of inverse imaging tasks.