How to get from input depth to output depth in convnets?

Question

See this example: convnet quiz Udacity.
How to get from input depth = 3  to output depth = 8? My assumption: In this example we have 8 filter (kernels) and each of them slides over the 3 inputs. So in total we have 24 convolutions. That would give me a depth of 24? So how to reduce to eight?

Update: I found this mapping table by Yann. LeNet5, see page 8 Table1. However the question is, whether this table is still used in the same fashion as in early convnets or today we might use a different mapping sheme? E.g. just sum 3 filtered maps into one of the 8 output maps?

Ryan Zotti · Answer

After the input layer, depth is simply the number of filters. From the official Stanford course materials:

"The depth of the output volume is a hyperparameter: it corresponds to
  the number of filters we would like to use."

Source: http://cs231n.github.io/convolutional-networks/

How to get from input depth to output depth in convnets?

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