Questions about PSPNet. about pspnet

[lxtGH]

The output of segmentation map is 1/8 and use bilinear upsampling to recover the original size.

[shentanyue]

I have same question.

[alexcekay]

Hi there,

But I think the feature map size is 1/16 when you use ResNet50. Do you use only first 3 blocks of ResNet50?

To get 1/8 of the input size don't use a simple ResNet. You should use a DilatedResnet (https://arxiv.org/abs/1705.09914)

But after that, the image size is 1/8 of the input image. How did you resize them to the same image size as input image?

Yeah you're right there. Thats definitely not described well in the paper. For my implementation i did the following: Upscale all the pooling layers so that they have the same width/height as the output of the dilated resnet. Then concat them all. Add two convs and then upsample this 8 times to get the original image size

[qizhuli]

@kazucmpt @shentanyue These are probably best clarified by referring to the official code. (And a good thing about Caffe is that the network architecture is fully and clearly laid out in a human-friendly text file ;P)

In the very end of their provided network definition files (see evaluation/prototxt directory), you will see that their networks are terminated with an Interp layer that upsamples the bottom blob by 8 times spatially:

layer {
  name: "conv6_interp"
  type: "Interp"
  bottom: "conv6"
  top: "conv6_interp"
  interp_param {
    zoom_factor: 8
  }
}

And if you would like more details on the Interp layer, you can check out its source code.

[allendred]

Would the upsample layer replace interp layer ?
My device do not support it.

[Abhishek2028]

Hi, Here in this architecture we created bins of sizes 1x1x512->1x1x1, 2x2x1, 3x3x1, 6x6x1.
1/8 of original feature map is 28.
How to Upsample features from 3x3 to 28x28. I tried with so many integer values. How to do upsampling