I think figure 2 is trying to show how the convolution operation is happening inside the convolution layer.
I made a diagram based off my understanding of convnets to try and help
conv851×412 11.9 KB
There are two filters in the network as out_channel = 2.
in_channel = 2 and kernel_size = 3 therefore filters are of size [3 x 3 x 2].
In my diagram it show 2 [3 x 3 x 2] filters performing the convolution operation on the same input image. You have 4 tensor outputs because there are 4 [3 x 3] kernels.

EDIT:
The output of this operation is a feature map of size:
(𝑊−𝐹+2𝑃)/𝑆+1
𝑊 is the input volume
𝑃 is padding
𝐹 is filter size
𝑆 is stride

Hope this helps!