Comments (11)
Thanks for your interest in our work!
It is just a showcase. Our method could handle the incomplete problem of different missing rates and you can change it in configure.py.
from 2021-cvpr-completer.
As in the code, the missing rate is seemed to be determined in the get_mask function.
However, if I comment out this line, or change the missing rate to 1
in configure.py, the code will fail to reproduce the results under the incomplete setting (i.e. missing rate = 0.5
).
from 2021-cvpr-completer.
The masked data is generated by the get_mask function and the corresponding missing rate is in configure.py. It should be pointed that the missing rate in configure.py is the real missing rate as talked about in the main paper. For the line missing_rate = missing_rate / 2, it is the process of generating incomplete multi-view datasets.
By the way, our method is trained on the complete multi-view data thus cannot handle the situation with missing rate=1.
from 2021-cvpr-completer.
Well, you're right as I compute the missing from the resultant mask and it's around 0.5
.
I guess you did that halving because there are 2
views and you want them each bear 0.25
missing rate. And I suggest using:
missing_rate = missing_rate / view_num
which may be clearer.
from 2021-cvpr-completer.
Thanks for your suggestions! I have changed the code to missing_rate = missing_rate / view_num now.
from 2021-cvpr-completer.
Hi, I would like to ask if running a dataset with the missing rate set to 0, is it a complete view network model?
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Hi, I would like to ask if running a dataset with the missing rate set to 0, is it a complete view network model?
Yes it is~
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Thank you very much for your reply,
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你好,我发现Competer网络只能跑两个视图的数据集超过两个视图就不可以了,请问是不是这样的呢?
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Exactly. You could refer to our multi-view version DCP.
from 2021-cvpr-completer.
Thank you very much for your reply!
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Related Issues (11)
- a typo in the Autoencoder class HOT 1
- Why is Gaussian distribution? HOT 2
- about baseline AE2-Nets HOT 1
- 关于自动编码器层 HOT 4
- 关于损失函数 HOT 5
- 关于NoisyMNIST数据集的第一个view HOT 1
- 关于CL loss与Reconstruction loss,Dual prediction loss大小差距的问题 HOT 1
- 最大化互信息和对比学习的相关实验 HOT 2
- Require supplementary material HOT 1
- Dear author, it seems that this code can only execute two view data. Do you have a multi view version? HOT 3
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from 2021-cvpr-completer.