| Authors | O. O. Nedrejord, V. Thambawita, S. Hicks, P. Halvorsen and M. Riegler |
| Title | Vid2Pix - A Framework for Generating High-Quality Synthetic Videos |
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Status | Published |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | 2020 IEEE International Symposium on Multimedia (ISM) |
| Publisher | IEEE |
| Abstract | Data is arguably the most important resource today as it fuels the algorithms powering services we use every day. However, in fields like medicine, publicly available datasets are few, and labeling medical datasets require tedious efforts from trained specialists. Generated synthetic data can be to future successful healthcare clinical intelligence. Here, we present a GAN-based video generator demonstrating promising results. |
| Citation Key | 27576 |
