用无镜头相机和神经渲染技术，轻松实现多视角显示校准。
Learned Display Radiance Fields with Lensless Cameras
- 设计无镜头相机与隐式神经表征结合的采集方案
- 在46.6°×37.6°视角范围内重建显示光场
- 适合内容创作者快速完成显示校准，无需专业设备
显示校准是内容创作者维持视觉体验的关键任务，但通常需专用设备和暗室环境，难以普及。为消除硬件依赖，本文提出一种无镜头相机与基于隐式神经表示的算法协同设计的新方法，可从46.6°×37.6°的观察锥内高效重建显示器发出的光场。该方案为实现无感显示校准与表征迈出关键一步。
原文摘要 · Abstract (English)
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° X 37.6°. Our emerging pipeline paves the initial steps towards effortless display calibration and characterization.
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