Super-resolution face image by using reference facial images with HIME
Super-resolution face image by using reference facial images with HIME
HIME: Efficient Headshot Image Super-Resolution with Multiple Exemplars
arXiv paper abstract https://arxiv.org/abs/2203.14863v1
arXiv PDF paper https://arxiv.org/pdf/2203.14863v1.pdf
A promising direction for recovering the lost information in low-resolution headshot images is utilizing a set of high-resolution exemplars from the same identity.
Complementary images in the reference set can improve the generated headshot ... However ... quality and alignment of each exemplar cannot be guaranteed.
Using low-quality and mismatched images as references will impair the output results.
... propose an efficient Headshot Image Super-Resolution with Multiple Exemplars network (HIME) method.
... network can effectively handle the misalignment between the input and the reference without requiring facial priors and learn the aggregated reference set representation in an end-to-end manner.
... demonstrate ... framework not only has significantly fewer computation ... but also achieves better qualitative and quantitative performance.
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