Structure-Preserving Image Super-resolution (SPSR)
Yukai Shi, Keze Wang, Chongyu Chen, Li Xu and Liang Lin. Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning. To appear in IEEE Transactions on Mulitmedia (TMM), 2017. Paper
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The efficiency analysis for the scaling factor of 3 on the Set5 dataset. The evaluation platform is a high performance desktop (CPU 4.0GHz, 32GB, GTX 1080). Our proposed SPSR is written in TensorFlow and fully optimized by the Factorized CNN
Quantitative comparisons among different methods in terms of PSNR (dB), in which the underline indicates the second place and bold face represents the first place.
Quantitative comparisons among different methods in terms of SSIM, in which the underline indicates the second place and bold face represents the first place.
Visual comparison on the “Zebra” image from Set14 (factor 3), where the PSNR and SSIM are separated by “/”.
Visual comparisons on the “Butterfly” image from Set5 (factor 4), where the PSNR and SSIM are separated by “/”.
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