SSR2: Sparse signal recovery for single-image super-resolution on faces with extreme low resolutions
Pattern Recognition, pp. 308-324, 2019.
Abstract Automatic face recognition in the wild still suffers from low-quality, low resolution, noisy, and occluded input images that can severely impact identification accuracy. In this paper, we present a novel technique to enhance the quality of such extreme low-resolution face images beyond the current state of the art. We model the...More
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