Neural radiance fields-based holography [Invited]
<|reference_start|>Neural radiance fields-based holography [Invited]: 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.<|reference_end|>
@article{kang2024neural,
    title={Neural radiance fields-based holography [Invited]},
    author={Minsung Kang and Fan Wang and Kai Kumano and Tomoyoshi Ito and
  Tomoyoshi Shimobaba},
    journal={arXiv preprint arXiv:2403.01137},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.01137},
    primaryClass={cs.CV cs.GR eess.IV}
}