Holography stands at the forefront of visual technology innovation, offering immersive, three-dimensional visualizations through the manipulation of light wave amplitude and phase. Contemporary research in hologram generation has predominantly focused on image-to-hologram conversion, producing holograms from existing images. These approaches, while effective, inherently limit the scope of innovation and creativity in hologram generation. In response to this limitation, we present Holo-VQVAE, a novel generative framework tailored for phase-only holograms (POHs). Holo-VQVAE leverages the architecture of Vector Quantized Variational AutoEncoders, enabling it to learn the complex distributions of POHs. Furthermore, it integrates the Angular Spectrum Method into the training process, facilitating learning in the image domain. This framework allows for the generation of unseen, diverse holographic content directly from its intricately learned latent space without requiring pre-existing images. This pioneering work paves the way for groundbreaking applications and methodologies in holographic content creation, opening a new era in the exploration of holographic content.

Holo-VQVAE是一种新的生成框架，专门用于创建相位全息图。它结合了矢量量化变分自动编码器（Vector Quantized Variational AutoEncoders）的架构和角谱方法（Angular Spectrum Method）的训练过程，从而能够直接从其复杂学习的潜在空间中生成前所未见的多样化全息内容，为全息内容创作的突破性应用和方法铺平了道路，开启了全息内容探索的新时代。

Holo-VQVAE：用于纯相全息图的VQ-VAE