SSR2: Sparse signal recovery for single-image super-resolution on faces with extreme low resolutions

Pattern Recognition, pp. 308-324, 2019.

Cited by: 9|Views23
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Abstract:

•This paper introduces a novel technique to extract a sparse feature vector from extreme low resolution face images. This feature vector enables us to synthesize a high-resolution face image with magnification factors up to 16x from a single input face. We show how our method is robust to noise and handles real-world low-resolution faces....More

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