Progressive Face Super-Resolution via Attention to Facial Landmark
Deokyun Kim (Korea Advanced Institute of Science and Technology), Minseon Kim (Korea Advanced Institute of Science and Technology), Gihyun Kwon (Korea Advanced Institute of Science and Technology), Daeshik Kim (Korea Advanced Institute of Science and Technology) AbstractFace Super-Resolution (SR) is a subfield of the SR domain that specifically targets the reconstruction of face images. The main challenge of face SR is to restore essential facial features without distortion. We propose a novel face SR method that generates photo-realistic 8× super-resolved face images with fully retained facial details. To that end, we adopt a progressive training method, which allows stable training by splitting the network into successive steps, each producing output with a progressively higher resolution. We also propose a novel facial attention loss and apply it at each step to focus on restoring facial attributes in greater details by multiplying the pixel difference and heatmap values. Lastly, we propose a compressed version of the state-of-the-art face alignment network (FAN) for landmark heatmap extraction. With the proposed FAN, we can extract the heatmaps suitable for face SR and also reduce the overall training time. Experimental results verify that our method outperforms state-of-the-art methods in both qualitative and quantitative measurements, especially in perceptual quality.
DOI
10.5244/C.33.161
https://dx.doi.org/10.5244/C.33.161
Files
BibTeX
@inproceedings{BMVC2019,
title={Progressive Face Super-Resolution via Attention to Facial Landmark},
author={Deokyun Kim and Minseon Kim and Gihyun Kwon and Daeshik Kim},
year={2019},
month={September},
pages={161.1--161.12},
articleno={161},
numpages={12},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
publisher={BMVA Press},
editor={Kirill Sidorov and Yulia Hicks},
doi={10.5244/C.33.161},
url={https://dx.doi.org/10.5244/C.33.161}
}
title={Progressive Face Super-Resolution via Attention to Facial Landmark},
author={Deokyun Kim and Minseon Kim and Gihyun Kwon and Daeshik Kim},
year={2019},
month={September},
pages={161.1--161.12},
articleno={161},
numpages={12},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
publisher={BMVA Press},
editor={Kirill Sidorov and Yulia Hicks},
doi={10.5244/C.33.161},
url={https://dx.doi.org/10.5244/C.33.161}
}