I know this problem was posted a while back and I am currently working on sensor/feature fusion. I used torch.cat to use the output features of certain layers of my network. However, I have recently seen an example where the fusion was achieved by simply adding the two output features. Something like this:
def forward(self,input):
        conv_1 = self.conv_1(input)
        conv_2 = self.conv_2(conv_1)
        res = conv_1 + conv_2
        conv_3 = self.conv_3(res)
        return conv_3

Could some be able to confirm which method is better for my problem? Thanks in advance.