Question about SSD visualization

[villanuevab]

Since the prediction convolutions are separate from the convolutions that feed forward to the next (conv) layers, during backprop, some prediction layer X will receive weight updates for:
(1) its classification prediction conv weights
(2) its regression conv weights
(3) its normal conv weights that feed into later layers

Thus, for another earlier-during-foward-pass/later-during-backward-pass prediction layer X', the weights will be updated as follows:
(1) classification prediction conv weights are updated from output layer
(2) regression prediction conv weights are updated from output layer
(3) normal conv weights are updated with normal conv weights of X

True/false? The included diagram for SSD 300 seems to support this intuition.