Multigrid Backprojection Super Resolution

Pablo Navarrete Michelini, Dan Zhu and Hanwen Liu

Citation

Pablo Navarrete Michelini, Hanwen Liu and Dan Zhu, "Multigrid Backprojection Super-Resolution and Deep Filter Visualization", to appear in the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)

Pablo Navarrete Michelini, Dan Zhu and Hanwen Liu, "Multi-Scale Recursive and Perception-Distortion Controllable Image Super-Resolution", in The European Conference on Computer Vision Workshops (ECCVW), 2018.

BibTeX MGBP (AAAI-19)

@inproceedings{MGBP,
    title        = {Multigrid Backprojection Super--Resolution and Deep Filter Visualization},
    author       = {Navarrete~Michelini, Pablo and Liu, Hanwen and Zhu, Dan},
    booktitle    = {Proceedings of the Thirty--Third AAAI Conference on Artificial Intelligence (AAAI 2019)},
    year         = {2019},
    organization = {AAAI},
    url          = {http://arxiv.org/abs/1809.09326}
}

BibTeX Generative MGBP (ECCVW)

@inproceedings{G-MGBP,
    author    = {Navarrete~Michelini, Pablo and Liu, Hanwen and Zhu, Dan},
    title     = {Multi--Scale Recursive and Perception--Distortion Controllable Image Super--Resolution},
    booktitle = {The European Conference on Computer Vision Workshops (ECCVW)},
    month     = {September},
    year      = {2018},
    url       = {http://arxiv.org/abs/1809.10711}
}

PIRM-2018 Output Images

• 4✕ Test set BOE-R3 (2^nd place) (63.2MB)
• 4✕ Test set BOE-R2 (5^th place) (48.8MB)
• 4✕ Test set BOE-R1 (7^th place) (45.3MB)

Instructions:

• Copy low resolution images from the test set in input_images (provided as empty directory)
• Run python main.py
• Upscale images will come out in output_images (automatically created and cleaned if already exists)
• By default BOE-R3 model is used. The GPU number and model parameters can be changed in main.py.

Requirements:

• Python 3, PyTorch, NumPy, Pillow