[D] Role of the Identity Matrix in PointNet's Input Transformation Block

Hello,

I'm currently exploring the code for PointNet, specifically the Input Transformation block. I understand that this block is used to learn transformation matrices that are applied to the input point cloud, but I'm a bit confused about the role of the identity matrix in this context and generally in deep learning

Here's a snippet of the code that I'm referring to:

    def forward(self, x):
        batchsize = x.size()[0]
        x = F.relu(self.bn1(self.conv1(x)))
        x = F.relu(self.bn2(self.conv2(x)))
        x = F.relu(self.bn3(self.conv3(x)))
        x = torch.max(x, …

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