NeRF as super-resolution method
dc.contributor.advisor | van Bergen, R.S. | |
dc.contributor.advisor | Kietzmann, T.C. | |
dc.contributor.author | Berberich, Sven | |
dc.date.issued | 2021-06-18 | |
dc.description.abstract | This thesis is concerning itself with the question whether Neural radiance elds (NeRF) can be used to perform super-resolution. The NeRF method learns a scene representation by receiving images of said scene to train on. As this representation receives information from multiple images we hy- pothesise that the learned representation contains more information than a single image does and could thus create accurate high-resolution outputs while only training on low-resolution images. We observe that the creation of HR images is quite possible, the quality of these is however, only in very limited situations, comparable with interpo- lation based super-resolution methods and signi cantly worse then state-of- the-art methods. | en_US |
dc.identifier.uri | https://theses.ubn.ru.nl/handle/123456789/12759 | |
dc.language.iso | en | en_US |
dc.thesis.faculty | Faculteit der Sociale Wetenschappen | en_US |
dc.thesis.specialisation | Bachelor Artificial Intelligence | en_US |
dc.thesis.studyprogramme | Artificial Intelligence | en_US |
dc.thesis.type | Bachelor | en_US |
dc.title | NeRF as super-resolution method | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Berberich, S. s-1006248-BSc-Thesis-2021.pdf
- Size:
- 4.21 MB
- Format:
- Adobe Portable Document Format