Name
Abstract | ||
|---|---|---|
Most of the methods for repairing old photos today are to manually process them using image editing software, such as Photoshop. The time of manual repairing is directly proportional to the damage degree of the photo, which is time consuming and laborious. Therefore, this paper proposes a two-stage convolution network to automatically repair damaged old photos. The first stage will detect the damaged areas of the photos, and the second stage will repair these areas. The experiment results demonstrates our method can successfully detect and repair the damage of the photos. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ISPACS48206.2019.8986336 | 2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) |
Keywords | Field | DocType |
Damaged old photos,Image repariment,Image restoration,Image inpainting,Convolutional Neural Network | Computer vision,Computer science,Convolution,Convolutional neural network,Artificial intelligence,Graphics software,Image restoration | Conference |
ISSN | ISBN | Citations |
2642-3510 | 978-1-7281-3039-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tien-Ying Kuo | 1 | 148 | 19.24 |
| Yu-Jen Wei | 2 | 0 | 1.01 |
| Ming-Jui Lee | 3 | 0 | 0.34 |
| Tzu-Hao Lin | 4 | 5 | 1.85 |