articleACM Transactions on GraphicsNov 27, 2020Closed access

Neural holography with camera-in-the-loop training

Stanford University

Indexed incrossref

Abstract

Holographic displays promise unprecedented capabilities for direct-view displays as well as virtual and augmented reality applications. However, one of the biggest challenges for computer-generated holography (CGH) is the fundamental tradeoff between algorithm runtime and achieved image quality, which has prevented high-quality holographic image synthesis at fast speeds. Moreover, the image quality achieved by most holographic displays is low, due to the mismatch between the optical wave propagation of the display and its simulated model. Here, we develop an algorithmic CGH framework that achieves unprecedented image fidelity and real-time framerates. Our framework comprises several parts, including a novel…

Citation impact

485
total citations
FWCI
43.41
Percentile
100%
References
69
Citations per year

Authors

4

Topics & keywords

Keywords
  • Holography
  • Holographic display
  • Computer science
  • High fidelity
  • Computer-generated holography
  • Artificial intelligence
  • Computer vision
  • Artificial neural network
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