Name
Abstract | ||
|---|---|---|
Shearlet Transform (ST) is one of the most effective approaches for light field reconstruction from Sparsely-Sampled Light Fields (SSLFs). This demo paper presents a comprehensive implementation of ST for light field reconstruction using one of the most popular machine learning libraries, i.e. Tensor Flow. The flexible architecture of TensorFlow allows for the easy deployment of ST across different platforms (CPUs, GPUs, TPUs) running varying operating systems with high efficiency and accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICMEW.2019.00116 | 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW) |
Keywords | Field | DocType |
Light Field Reconstruction,Shearlet Transform,TensorFlow,Epipolar-Plane Image,Light Field Sparsification | Computer vision,Architecture,Software deployment,Tensor,Computer science,Shearlet transform,Light field,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
2330-7927 | 978-1-5386-9215-8 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Gao | 1 | 0 | 1.01 |
| Reinhard Koch | 2 | 2038 | 170.17 |
| Robert Bregovic | 3 | 148 | 18.84 |
| Harlyn Baker | 4 | 28 | 7.89 |