Multi Object Detection
Because a NN doesn't see a box. The only job it does is to minimize the loss using Feedforward and Backpropagation.

Let's say the image has 1 object - 
=> 4 o/p values => 4 o/p neurons => 4 y_train values => 4 losses into the NN
=>To have the loss minimum it will adjust itself to have all the 4 o/p neurons as close to the truth as posible.

Let's say the image has 2 object -
=> 8 o/p values => 8 o/p neurons => 8 y_train values => 8 losses into the NN
=>To have the loss minimum it will adjust itself to have all the 8 o/p neurons as close to the truth as posible.

The difference - Obviously, later will be a bigger network and need more epochs to get the golden values of weights

If you have just started Deep Learning - 
Michael Nielsen