Тёмный

Time-multiplexed Neural Holography | SIGGRAPH 2022 

Stanford Computational Imaging Lab
Подписаться 4,2 тыс.
Просмотров 3,5 тыс.
50% 1

Project website: www.computationalimaging.org/...
Abstract:
Holographic near-eye displays offer unprecedented capabilities for virtual and augmented reality systems, including perceptually important focus cues. Although artificial intelligence-driven algorithms for computer-generated holography (CGH) have recently made much progress in improving the image quality and synthesis efficiency of holograms, these algorithms are not directly applicable to emerging phase-only spatial light modulators (SLM) that are extremely fast but offer phase control with very limited precision. The speed of these SLMs offers time multiplexing capabilities, essentially enabling partially-coherent holographic display modes. Here we report advances in camera-calibrated wave propagation models for these types of near-eye holographic displays and we develop a CGH framework that robustly optimizes the heavily quantized phase patterns of fast SLMs. Our framework is flexible in supporting runtime supervision with different types of content, including 2D and 2.5D RGBD images, 3D focal stacks, and 4D light fields. Using our framework, we demonstrate state-of-the-art results for all of these scenarios in simulation and experiment.

Наука

Опубликовано:

 

6 авг 2024

Поделиться:

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист
Посмотреть позже
Комментарии : 3   
Далее
Neural Holography 3D | SIGGRAPH Asia 2021
5:33
Просмотров 2,8 тыс.
Разоблачение ушные свечи
00:28
Просмотров 736 тыс.
Time Multiplexed Coded Aperture Imaging | ICCV 2021
8:31
Beyond the Metaverse - Towards Human-centric XR
26:44
Просмотров 1,2 тыс.
SIGGRAPH 2022 Technical Papers Preview
4:08
Просмотров 39 тыс.
Eye Tracking Revisited
34:33
Просмотров 7 тыс.
The moment we stopped understanding AI [AlexNet]
17:38
Просмотров 857 тыс.
SIGGRAPH 2021: Technical Papers Preview Trailer
4:04
Это iPhone 16
0:52
Просмотров 924 тыс.
Проверил, как вам?
0:58
Просмотров 378 тыс.