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Computer Science > Computer Vision and Pattern Recognition
Title: Neural radiance fields-based holography [Invited]
(Submitted on 2 Mar 2024 (v1), last revised 9 May 2024 (this version, v2))
Abstract: This study presents a novel approach for generating holograms based on the neural radiance fields (NeRF) technique. Generating three-dimensional (3D) data is difficult in hologram computation. NeRF is a state-of-the-art technique for 3D light-field reconstruction from 2D images based on volume rendering. The NeRF can rapidly predict new-view images that do not include a training dataset. In this study, we constructed a rendering pipeline directly from a 3D light field generated from 2D images by NeRF for hologram generation using deep neural networks within a reasonable time. The pipeline comprises three main components: the NeRF, a depth predictor, and a hologram generator, all constructed using deep neural networks. The pipeline does not include any physical calculations. The predicted holograms of a 3D scene viewed from any direction were computed using the proposed pipeline. The simulation and experimental results are presented.
Submission history
From: Tomoyoshi Shimobaba Prof. [view email][v1] Sat, 2 Mar 2024 08:49:02 GMT (16309kb,D)
[v2] Thu, 9 May 2024 23:59:40 GMT (17436kb,D)
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