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According to your paper, the "Interp" layer does a bilinear interpolation to upsample its previous layer's output. But "Interp" layer has two inputs in your implementation. I'm not very familiar with caffe. Could you provide some documentations of "Interp" layer in caffe? Is there any alternatives in tensorflow or pytorch?
The text was updated successfully, but these errors were encountered:
The first input to the layer is the Tensor to be resized, the second input dictates the target size. In Tensorflow, you can use tf.image.resize_images with Bilinear interpolation.
According to your paper, the "Interp" layer does a bilinear interpolation to upsample its previous layer's output. But "Interp" layer has two inputs in your implementation. I'm not very familiar with caffe. Could you provide some documentations of "Interp" layer in caffe? Is there any alternatives in tensorflow or pytorch?
The text was updated successfully, but these errors were encountered: