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.
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