Photonics Research, Volume. 12, Issue 12, 2747(2024)
Physics-aware cross-domain fusion aids learning-driven computer-generated holography
[14] M. Zhou, S. Jiao, P. Chakravarthula. Point spread function-inspired deformable convolutional network for holographic displays. Proc. SPIE, 13104, 131042M(2024).
[16] G. A. Koulieris, K. Akşit, M. Stengel. Near-eye display and tracking technologies for virtual and augmented reality. Computer Graphics Forum, 38, 493-519(2019).
[18] R. W. Gerchberg. A practical algorithm for the determination of plane from image and diffraction pictures. Optik, 35, 237-246(1972).
[36] O. Ronneberger, P. Fischer, T. Brox. U-net: Convolutional networks for biomedical image segmentation. Medical Image Computing and Computer-Assisted Intervention, 234-241(2015).
[40] J. Johnson, A. Alahi, F.-F. Li. Perceptual losses for real-time style transfer and super-resolution. Proceedings of European Conference of Computer Vision, 694-711(2016).
[41] E. Agustsson, R. Timofte. Ntire 2017 challenge on single image super-resolution: dataset and study. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 126-135(2017).
[42] Z. Dong, J. Jia, Y. Li. Divide-conquer-and-merge: memory- and time-efficient holographic displays. IEEE Conference Virtual Reality and 3D User Interfaces (VR), 493-501(2024).
Get Citation
Copy Citation Text
Ganzhangqin Yuan, Mi Zhou, Fei Liu, Mu Ku Chen, Kui Jiang, Yifan Peng, Zihan Geng, "Physics-aware cross-domain fusion aids learning-driven computer-generated holography," Photonics Res. 12, 2747 (2024)
Category: Holography, Gratings, and Diffraction
Received: Apr. 19, 2024
Accepted: Aug. 17, 2024
Published Online: Nov. 12, 2024
The Author Email: Zihan Geng (geng.zihan@sz.tsinghua.edu.cn)
CSTR:32188.14.PRJ.527405