Holographic displays are considered to be promising technologies for augmented and virtual reality devices. Using spatial light modulators (SLMs), they can directly modulate the wavefront of light. Through the modulation of the wavefront, they can provide observers three-dimensional imagery. However, they suffer from a large computation load, and it is important to overcome the disadvantage for the popularization of holographic display techniques. In this invited paper, we adopt a deep learning algorithm for the fast generation of computer-generated holograms (CGHs). We propose the deep neural network designed for the generation of complex holograms. The overall algorithm for the learning-based generation of CGHs using the network is introduced, and the training strategy is provided. The simulation and experimental results are demonstrated, and we verified the feasibility of using the deep learning algorithm for CGH computation.
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