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The Module of MaxPool3dTFPadding with kernel_size=(1,3,3), stride(1,2,2) can lead to asymmetrical padding.
It would influence the output feature map, as the bottom right would be usually higher than other part of the feature map.
When I try to input a all zeros tensor into I3D model pretrained on Kinetics-400, someting strange happen, I average pooling the C and T dim and min-max norm to get a picture as below. The bottom right is much higher than other parts.
By checking each layer output, I find out bottom right is usually have higher activation value than other part but not obvious, until mixed_5b block.
I don't know whether it hurt the model's performance, but at least it hurt the Interpretability.
The text was updated successfully, but these errors were encountered:
Interesting ! I am not sure whether this is influencing the numerical results as I converted the models by checking that the results were consistent on different images.
I did observe a slight discrepancy with the original model (as reported in the readme) maybe this is related !
The Module of MaxPool3dTFPadding with kernel_size=(1,3,3), stride(1,2,2) can lead to asymmetrical padding.
It would influence the output feature map, as the bottom right would be usually higher than other part of the feature map.
When I try to input a all zeros tensor into I3D model pretrained on Kinetics-400, someting strange happen, I average pooling the C and T dim and min-max norm to get a picture as below. The bottom right is much higher than other parts.
By checking each layer output, I find out bottom right is usually have higher activation value than other part but not obvious, until mixed_5b block.
I don't know whether it hurt the model's performance, but at least it hurt the Interpretability.
The text was updated successfully, but these errors were encountered: