Accurate Image Super-Resolution Using Very Deep Convolutional Networks
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Cites background or methods from "Accurate Image Super-Resolution Usi..."
...SRResNet is a ResNet architecture [18] based CNN model proposed by Ledig et al. [26] which goes deeper than VDSR for better performance....
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...They propose a diversity of ideas and design details and generally build upon and go beyond the very recent proposed SR works [10, 49, 21, 26]....
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...The performance of the top methods have continuously improved [54, 48, 21, 26] as the field has reached maturity....
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...Most of the recent SR works adopted a couple of datasets like the 91 train images 23 24 25 26 27 28 29 30 31 32 33 34 35 bicubic A+ ACCV14 [48] SelfEx CVPR15 [19] ARFL+ CVPR15 [39] PSyCo CVPR16 [33] IA CVPR16 [49] WSDSR arxiv17 [7] SRCNN PAMI16 [10] CSCN-MV ICCV16 [51] ESPCN CVPR16 [42] FSRCNN ECCV16 [11] VDSR CVPR16 [21] DRCN CVPR16 [22] DRRN CVPR17 [44] SRResNet CVPR17 [26] Lab402 CVPRW17 [46] HelloSR CVPRW17 [46] SNU CVPRW17 [46]...
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...VDSR is a VGG16 architecture [43] based CNN model proposed by Kim et al. [21]....
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2,090 citations
2,025 citations
Cites background or methods from "Accurate Image Super-Resolution Usi..."
...Manga109 (4×): YumeiroCooking HR Bicubic SRCNN [1] FSRCNN [2] VDSR [4] PSNR/SSIM 24....
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...proposed VDSR [4] and DRCN [19] with 20 layers and achieved significant improvement in accuracy....
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...VDSR [4] IRCNN [15] SRMDNF [11] RDN [17] RCAN 22....
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...Urban100 (8×): img 040 HR Bicubic SRCNN [1] SCN [3] VDSR [4] PSNR/SSIM 15....
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...HR Bicubic SRCNN [1] FSRCNN [2] SCN [3] VDSR [4] DRRN [5]...
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1,872 citations
References
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