Glasses-free 3D display with ultrawide viewing range using deep learning
Glasses-free three-dimensional (3D) displays provide users with an immersive visual experience without the need of any wearable devices<sup>1,2</sup>. To achieve high-quality 3D imaging, a display should have both large linear dimensions and a wide viewing angle. However, the trade-off between spatial extent and bandwidth of optical systems, the space-bandwidth product, conventionally constrains the simultaneous maximization of the two. The two most common approaches to 3D displays are holographic<sup>3,4</sup> and automultiscopic<sup>1,5,6</sup>, which, respectively, sacrifice either scale or viewing angle. Recently, some implementations enhanced by artificial intelligence have shown directions to mitigate these constraints, but they still operate within a set space-bandwidth product<sup>7,8</sup>. As a result, it remains challenging to fabricate large-scale wide-angle 3D displays<sup>9</sup>. Here we report the realization of a large-scale full-parallax 3D display with seamless viewing beyond 100°, maintained at over 50 Hz and 1,920 × 1,080 resolution on a low-cost light-field delivery setup. This device, called EyeReal, is realized by accurately modelling binocular view and combining it with a deep-learning real-time optimization, enabling the generation of optimal light-field outputs for each of the eyes. Our device could potentially enable applications in educational tools, 3D design and virtual reality<sup>10,11</sup>.
Authors
- Han-Sen Zhong (ORCID: https://orcid.org/0000-0001-9844-8214)
- Wanli Ouyang (ORCID: https://orcid.org/0000-0002-9163-2761)
- Canyu Zhao (ORCID: https://orcid.org/0009-0002-4142-6844)
- Weijie Ma (ORCID: https://orcid.org/0000-0003-0395-3336)
- Zhang-Rui Zhao (ORCID: https://orcid.org/0009-0001-4250-4966)
Institutions
- Zhejiang University of Science and Technology (CN)
- Chinese University of Hong Kong (HK)
- Fudan University (CN)
- Shanghai Innovative Research Center of Traditional Chinese Medicine (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Shanghai Artificial Intelligence Laboratory (CN)
- Beihang University (CN)
Publication Details
- Journal
- Nature
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1038/s41586-025-09752-y
- Citations
- 4
- Primary Topic
- Advanced Optical Imaging Technologies
- Type
- article
- Field-Weighted Citation Impact
- 4.54