Neural Plenoptic Sampling: Learning Light-field from Thousands of Imaginary Eyes

Junxuan Li, Yujiao Shi, Hongdong Li

Abstract:

Proposed a neural representation for the plenoptic function, which describes light rays observed from any given position in every viewing direction.
Proposed proxy depth reconstruction and color-blending network for achieving well approximation on the complete plenoptic function.
The generated results are in high-quality with better PSNR than previous methods. The training and testing time of proposed method is also more than 10 times faster than prior works.