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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