I'm not sure this is overfitting but a very narrow training set. It's still generalising against inputs it hasn't seen. If it was really overfitted then it woul

I'm not sure this is overfitting but a very narrow training set. It's still generalising against inputs it hasn't seen. If it was really overfitted then it wouldn't work for any unseen frames and it would be learning the "noise". It's not learning noise else you'd get lots of false positives, such as dark areas in the frame that look a bit like Batman but aren't. The main reason you want to generalise is noise rejection (no mention of this in the article). I think the S/N ratio in a video is exceptionally high as the dataset is directly repeatable so the source of truth is exceptionally accurate. That being said, narrow training sets are a great idea and this application looks great.