1x1 Convolutional filter

I have a Nx1xHxW feature maps. I need to add a second head that generates Nx3xHxW representing pixel wise regression with a triplet for each pixel .

The question is: how would you go from Nx1xHxW to Nx3xHxW? A fully connected layer would be too expensive in terms of introduced parameters.

That’s what I am trying a 1x1x3 convolutional filter with stride 1 defined as nn.Conv2d(1, 3, (1, 1), stride=1, bias=True) but results does not seem encouraging. Any suggestion would be welcome.