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Real-ESRGAN super-resolution model from ruDALL-E
64,796 runs


This model runs predictions on Nvidia T4 GPU hardware.

80% of predictions complete within 61 seconds. The predict time for this model varies significantly based on the inputs.


This is the Real-ESRGAN super-resolution model from ruDALL-E.

Real-ESRGAN was created by Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan. Paper
Re-trained version of Real-ESRGAN was created by Igor Pavlov
ruDALL-E was created by Alex Shonenkov, Tatiana Shavrina, et al., at Sberbank AI


    author    = {Xintao Wang and Liangbin Xie and Chao Dong and Ying Shan},
    title     = {Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data},
    booktitle = {International Conference on Computer Vision Workshops (ICCVW)},
    date      = {2021}