Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

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Deep LearningMetaIQA
Overview

MetaIQA

  • PyTorch 0.4.1 (with Python 3.6.0) implementation of the following paper.

  • If you find our work is useful, pleaes cite our paper:
    @InProceedings{Zhu2020MetaIQA,
    author = {Zhu, Hancheng and Li, Leida and Wu, Jinjian and Dong, Weisheng and Shi, Guangming},
    title = {{MetaIQA:} Deep Meta-Learning for No-Reference Image Quality Assessment},
    booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {Jun.},
    pages ={14143--14152},
    year = {2020}
    }

  • MetaIQA_On_TID2013_KADID.py for quality prior model training.

  • MetaIQA_FineTune_WILDLIVE.py for model fine-tuning on LIVE challenge database.

  • If you want to train the quality prior model, you need download TID2013 and KADID-10K databases.

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