I try it, but the results are bad, you can see the details in this post.
I fiddle with different learning rate(start from 0.001, 0.0005, 0.00025), run more epoch(6 epoch) with three solutions I mentioned above, use different layers of vgg16 to extract features, all of them cannot train the network successful.
Loss of each batch are around 3~5, aggregate loss is 3~4, they are measure by mae summation of three vgg layers output(almost same as lesson 9). Loss value seem small(If my memory is correct, loss of super resolution more than 20 after 2 epoch), that means predicted output should be quite close to the original image, but when I try to colorize the image of training set, it give me bad results like this one
