Calibrating displays is a basic and regular task that content creators must perform to maintain optimal visual experience, yet it remains a troublesome issue. Measuring display characteristics from different viewpoints often requires specialized equipment and a dark room, making it inaccessible to most users. To avoid specialized hardware requirements in display calibrations, our work co-designs a lensless camera and an Implicit Neural Representation based algorithm for capturing display characteristics from various viewpoints. More specifically, our pipeline enables efficient reconstruction of light fields emitted from a display from a viewing cone of 46.6{\deg} X 37.6{\deg}. Our emerging pipeline paves the initial steps towards effortless display calibration and characterization.
@article{arxiv.2510.03356,
title = {Learned Display Radiance Fields with Lensless Cameras},
author = {Ziyang Chen and Yuta Itoh and Kaan Akşit},
journal= {arXiv preprint arXiv:2510.03356},
year = {2025}
}