Name
Abstract | ||
|---|---|---|
A face hallucination algorithm is proposed to generate high-resolution images from JPEG compressed low-resolution inputs by decomposing a deblocked face image into structural regions such as facial components and non-structural regions like the background. For structural regions, landmarks are used to retrieve adequate high-resolution component exemplars in a large dataset based on the estimated head pose and illumination condition. For non-structural regions, an efficient generic super resolution algorithm is applied to generate high-resolution counterparts. Two sets of gradient maps extracted from these two regions are combined to guide an optimization process of generating the hallucination image. Numerous experimental results demonstrate that the proposed algorithm performs favorably against the state-of-the-art hallucination methods on JPEG compressed face images with different poses, expressions, and illumination conditions. |
Year | DOI | Venue |
|---|---|---|
2018 | https://doi.org/10.1007/s11263-017-1044-4 | International Journal of Computer Vision |
Keywords | Field | DocType |
Face hallucination,Super resolution,JPEG compression,Image denoising,Landmark points | Computer vision,Face hallucination,Super resolution algorithm,Expression (mathematics),Computer science,JPEG,Image denoising,Artificial intelligence,Jpeg compression,Superresolution,Hallucinating | Journal |
Volume | Issue | ISSN |
126 | 6 | 0920-5691 |
Citations | PageRank | References |
2 | 0.35 | 23 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chih-Yuan Yang | 1 | 247 | 10.50 |
| Sifei Liu | 2 | 227 | 17.54 |
| Yang Ming-Hsuan | 3 | 15303 | 620.69 |