The first example looks like the “common” res net architecture, i.e. you add the residual before the block to its output.
I wouldn’t say it’s the right approach, as the second one also looks interesting. There you add the same residual to both block outputs. It looks a bit like Densely Connected Convolutional Networks 135.
Anyway, if you want to stick to a ResNet-lile architecture, the first approach looks good.