… • Learned holographic light transport. We propose a learned approach for holographic light
transport to bridge the gap between simulations and experimentation. Our method learns a …

… : • Learned focal surface light transport model. By uniquely leveraging SAC for CGH, we
introduce a new learned light trans… Our model identifies a mapping from a phase-only hologram …

… approximate “ideal” coherent light transport models for computing holograms. Instead, we
learn the deviations of the real display from the ideal light transport from the images measured …

… learning applications in digital holography (DH). Nevertheless, there remain huge potentials
in how deep learning … DH applications powered by deep learning algorithms. This article …

… In this work, we propose a new wave propagation model for light transport in a holographic
… plane-to-multiplane light transport. Similar to Peng et al. [2021; 2020], Chakravarthula et al. …

… incoherent holographic cameras, we propose a deep learning-based hologram filtering …
Our main goal is to generate complex-valued holograms based on the captured holograms …

… holographic models without translation symmetry, we demonstrate its ability to accurately
learn … By specifying the metric to be asymptotically AdS, we also train the Neural ODE to learn …

… Here we introduce a new hologram dataset, MIT-CGH-4K-V2… -quality 3D phase-only holograms.
The proposed system also … 3D holographic projections and discuss relevant spatial light …

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In this case we will assume that no light contribution from the plane can reach the hologram …

… holography. In this manuscript, I focus on the prosperous interactions between DNN and
holography. … to be in particular proficient for holographic reconstruction and computer-generated …