Regarding to paper: why learning will gives better result than the supervision itself?

[June01]

Hi,

Thanks for the nice work. I thought about the question a lot, but can't figure out why. If I may, can I take several minutes from you to answer that?

The thing is: I have the impression that, there are no shared parameters between localization branch and classification branch, so classification branch should be trained firstly, and then the localization branch, right? That is to say, OIC /layer or OIC selection is serving as the supervision for the localization branch. If all are correct, I don't understand why the autoloc result is better than the supervision(OIC selection)? How it outperforms the supervision if no shared parameters allowed?

That confused me a lot, and also hard for me to find the answer in the paper. I really appreciate it if you can help. Hope to get you back soon!

Thanks! June