Neural Light Field 3D Printing
Event Type
Technical Papers
Technical Papers Q&A
Registration Categories
TimeThursday, 10 December 202012:54 - 13:00 SGT
LocationZoom Room 3
DescriptionModern 3D printers are capable of printing large-size light-field displays at high-resolutions.
However, optimizing such displays in full 3D volume for a given light-field imagery is still a challenging task. Existing light field displays optimize over relatively small resolutions using a few co-planar layers in a 2.5D fashion to keep the problem tractable. In this paper, we propose a novel end-to-end optimization approach that encodes input light field imagery as a continuous-space implicit representation in a neural network. This allows fabricating high-resolution, attenuation-based volumetric displays that exhibit the target light fields. In addition, we incorporate the physical constraints of the material to the optimization such that the result can be printed in practice. Our simulation experiments demonstrate that our approach brings significant visual quality improvement compared to the multi-layer and uniform grid-based approaches. We validate our simulations with fabricated prototypes and demonstrate that our pipeline is flexible enough to print both planar and non-planar displays.