# Stochastic Light Field Holography

arXiv: https://arxiv.org/abs/2307.06277 · HTML: https://mlsanity.com/paper/2307.06277/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 77 references that are in the map.
- First posted on arXiv 12 Jul 2023.

## Builds on (most cited first, 16 of 16)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [PlenOctrees for Real-time Rendering of Neural Radiance Fields](https://mlsanity.com/paper/2103.14024/) (2021)
- [Phase recovery and holographic image reconstruction using deep learning in neural networks](https://mlsanity.com/paper/1705.04286/) (2017)
- [PhaseMax: Convex Phase Retrieval via Basis Pursuit](https://mlsanity.com/paper/1610.07531/) (2016)
- [Time-multiplexed Neural Holography: A flexible framework for holographic near-eye displays with fast heavily-quantized spatial light modulators](https://mlsanity.com/paper/2205.02367/) (2022)
- [Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation](https://mlsanity.com/paper/1610.04210/) (2016)
- [Neural 'Etendue Expander for Ultra-Wide-Angle High-Fidelity Holographic Display](https://mlsanity.com/paper/2109.08123/) (2021)
- [Gaze-Contingent Retinal Speckle Suppression for Perceptually-Matched Foveated Holographic Displays](https://mlsanity.com/paper/2108.06192/) (2021)
- [Multi-color Holograms Improve Brightness in Holographic Displays](https://mlsanity.com/paper/2301.09950/) (2023)
- [Alternating Projection, Ptychographic Imaging and Phase Synchronization](https://mlsanity.com/paper/1402.0550/) (2014)
- [Pupil-aware Holography](https://mlsanity.com/paper/2203.14939/) (2022)
- [Realistic Defocus Blur for Multiplane Computer-Generated Holography](https://mlsanity.com/paper/2205.07030/) (2022)
- [Waveguide Holography: Towards True 3D Holographic Glasses](https://mlsanity.com/paper/2211.02784/) (2022)
- [Simultaneous Color Computer Generated Holography](https://mlsanity.com/paper/2303.11287/) (2023)
- [Improving Acquisition Speed of X-Ray Ptychography through Spatial Undersampling and Regularization](https://mlsanity.com/paper/2105.09892/) (2021)
- [Characterizing the Immaterial. Noninvasive Imaging and Analysis of Stephen Benton's Hologram Engine no. 9](https://mlsanity.com/paper/2110.06080/) (2021)

## Built on by (most cited first, 3 of 3)

- [Complex-Valued Holographic Radiance Fields](https://mlsanity.com/paper/2506.08350/) (2025)
- [Maximum Likelihood Reconstruction for Multi-Look Digital Holography with Markov-Modeled Speckle Correlation](https://mlsanity.com/paper/2604.20154/) (2026)
- [Complex-Valued 2D Gaussian Representation for Computer-Generated Holography](https://mlsanity.com/paper/2511.15022/) (2025)

## Abstract (arXiv)

The Visual Turing Test is the ultimate goal to evaluate the realism of holographic displays. Previous studies have focused on addressing challenges such as limited 'etendue and image quality over a large focal volume, but they have not investigated the effect of pupil sampling on the viewing experience in full 3D holograms. In this work, we tackle this problem with a novel hologram generation algorithm motivated by matching the projection operators of incoherent Light Field and coherent Wigner Function light transport. To this end, we supervise hologram computation using synthesized photographs, which are rendered on-the-fly using Light Field refocusing from stochastically sampled pupil states during optimization. The proposed method produces holograms with correct parallax and focus cues, which are important for passing the Visual Turing Test. We validate that our approach compares favorably to state-of-the-art CGH algorithms that use Light Field and Focal Stack supervision. Our experiments demonstrate that our algorithm significantly improves the realism of the viewing experience for a variety of different pupil states.