[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment

Related tags

Deep Learning pytorch image-quality-assessment ntire2021
Overview

RADN

[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment

[Paper on arXiv]

Overview

Update

[2021/5/7] add codes for WResNet (our baseline).

Instruction

  1. run mkdir.sh to create necessary directories.

  2. use sh train.sh or sh test.sh to train or test the model. You can also change the options in the shell files as you like.

The pretrained models can be found at this URL.

Please note that the performance on the challenge leaderboard is obtained by ensembling and the checkpoint above is for the single model.

Performance

Scatter Plots

Attention Maps

Acknowledgment

The codes borrow heavily from WaDIQaM implemented by Dingquan Li and we really appreciate it.

Citation

If you find our work or code helpful for your research, please consider to cite:

@inproceedings{RADN2021ntire, 
title={Region-Adaptive Deformable Network for Image Quality Assessment}, 
author={Shuwei Shi and Qingyan Bai and Mingdeng Cao and Weihao Xia and Jiahao Wang and Yifan Chen and Yujiu Yang}, 
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops}, 
year={2021} 
}
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Comments
  • Request to answer questions

    Request to answer questions

    In test_val.py, the pre-trained model is "WResNet-lr=0.0001-bs=2-10". However, your released pre-trained in google drive is "WResNet-lr=0.0001-bs=2". What's the difference between these two pre-trained models.

    opened by happycaoyue 3
  • The following bugs appear in Deform model during debugging

    The following bugs appear in Deform model during debugging

    不太理解这部分的调用，错误也发生在这部分 I don't understand this part of the call，error also occur here torch.ops.torchvision.deform_conv2d（） 错误信息如下 The error message is as follows

    RuntimeError: torchvision::deform_conv2d() Expected a value of type 'Tensor' for argument 'bias' but instead found type 'int'.
Position: 4
Value: 1
Declaration: torchvision::deform_conv2d(Tensor input, Tensor weight, Tensor offset, Tensor mask, Tensor bias, int stride_h, int stride_w, int pad_h, int pad_w, int dilation_h, int dilation_w, int groups, int offset_groups, bool use_mask) -> (Tensor)
Cast error details: Unable to cast Python instance to C++ type (compile in debug mode for details)

    Looking forward to your reply

    opened by Oraclexu 2
  • 重新训练的时候发现RADN的结果都是nan，请问是什么原因？

    重新训练的时候发现RADN的结果都是nan，请问是什么原因？

    用RADN进行训练测试的结果如下： Validation Results - Epoch: 6 SROCC: nan KROCC: nan PLCC: nan RMSE: 119.7862 MAE: 93.5760 OR: 0.00% 而用WResNet的结果就在0.75左右，是不是RADN代码有问题？

    opened by lllllllllllll-llll 1
  • 关于contrastive pretraining strategy的提问

    关于contrastive pretraining strategy的提问

    作者您好，很感激您开源了你们这份代码，但是在其中有一些没明白的点，希望您能解惑一下： 论文中提到有利用孪生模型利用MOS分之间隐含的rank信息而不是单纯对MOS分做回归，会生成一波preference probabillity与预测分数si，然后与实际的prefenrece probabillity和实际分数算cross entrophy，但是在代码中好像没有看到这个。想知道在这个策略是用在最后来验证WResNet的性能还是用作WResNet的pretraining呢？

    opened by TowardsXY 0
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