Name
Title | ||
|---|---|---|
Neural 3D holography: learning accurate wave propagation models for 3D holographic virtual and augmented reality displays |
Abstract | ||
|---|---|---|
AbstractHolographic near-eye displays promise unprecedented capabilities for virtual and augmented reality (VR/AR) systems. The image quality achieved by current holographic displays, however, is limited by the wave propagation models used to simulate the physical optics. We propose a neural network-parameterized plane-to-multiplane wave propagation model that closes the gap between physics and simulation. Our model is automatically trained using camera feedback and it outperforms related techniques in 2D plane-to-plane settings by a large margin. Moreover, it is the first network-parameterized model to naturally extend to 3D settings, enabling high-quality 3D computer-generated holography using a novel phase regularization strategy of the complex-valued wave field. The efficacy of our approach is demonstrated through extensive experimental evaluation with both VR and optical see-through AR display prototypes. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3478513.3480542 | ACM Transactions on Graphics |
Keywords | DocType | Volume |
computational displays, holography, virtual reality, augmented reality | Journal | 40 |
Issue | ISSN | Citations |
6 | 0730-0301 | 1 |
PageRank | References | Authors |
0.37 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Suyeon Choi | 1 | 8 | 2.25 |
| Manu Gopakumar | 2 | 2 | 1.08 |
| Yifan Peng | 3 | 41 | 7.51 |
| Jonghyun Kim | 4 | 56 | 11.07 |
| Gordon Wetzstein | 5 | 945 | 72.47 |