Name
Abstract | ||
|---|---|---|
We propose a novel method based on Convolutional Neural Networks for content-preserving tone adjustment. The method is at the same time fast and accurate since we de couple the inference of the parameters and the color transform: the parameters are inferred from a down sampled version of the input image and the transformation is applied to the full resolution input. The method includes two steps of image enhancement: the first one is a global color transformation, while the second one is a local transformation. Experiments conducted on the DPED - DSLR Photo Enhancement Dataset, that has been used for the NTIRE19 Image Enhancement Challenge, and on the MIT-Adobe FiveK dataset, that is widely used for image enhancement, demonstrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CVPRW.2019.00245 | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
Field | DocType | ISSN |
Computer vision,Computer science,Artificial intelligence | Conference | 2160-7508 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simone Bianco | 1 | 226 | 24.48 |
| Cusano, C. | 2 | 114 | 5.11 |
| Flavio Piccoli | 3 | 16 | 2.09 |
| Raimondo Schettini | 4 | 1476 | 154.06 |