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ASPNet

An implementation of ASPNet, proposed in ATTENTION-GUIDED SECOND-ORDER POOLING CONVOLUTIONAL NETWORKS by Shannan Chen, Qiule Sun, Cunhua Li, Jianxin Zhang, Qiang Zhang

Now ASPNet (20, 34, 56) are implemented and the code is modified based on SENet

  • python cifar.py runs resnet20_ASP with Cifar10 and Cifar100 dataset.

Pre-requirements

  • Python>=3.7
  • PyTorch>=1.1
  • torchvision>=0.4

For training

To run cifar.py you need

  • pip install git+https://github.com/moskomule/homura

Results

Cifar10/100

python cifar.py [--baseline]
ResNet20 SENet20 ASPNet20 ResNet32 SENet32 ASPNet32
test accuracy (cifar10) 92.3% 92.6% 93.8% 93.2% 93.3% 94.6%
test accuracy (cifar100) 68.2% 69.1% 73.1% 69.7% 71.6% 74.2%

ImageNet

SENet18 ASPNet18 SENet34 ASPNet34
test accuracy (top1) 70.59% 72.16% 73.69% 74.83%

Contact

If you have any questions or suggestions, please contact me ([email protected]).

aspnet's People

Contributors

shannanchen avatar

Stargazers

Xa9aX ツ avatar  avatar Qiule Sun avatar MingMingCheng avatar

Watchers

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Forkers

mymuli

aspnet's Issues

关于论文公式(6) 的问题

非常感谢你们有意义的工作!

在阅读完论文和代码后,我有以下疑问:

对于论文NCEB章节中,公式(6)中使用 $f(x_{i},x_{j})=\theta (x_{i})^{T} \theta (x_{j})$ 来计算像素点i 与 像素点j 的关系,
仿照non-local的做法,一般使用torch.matmul(out1, out2)来计算,
但发现你们在代码里面使用MPN-COV方法 (改进池化的方法),

MPN_X_C = self.soca_c(out2_c)

对此,我想问一下,在这里为什么采用 MPN-COV方法 呢?可以从什么角度理解呢?

谢谢!

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