Yes, but historically this research is barely seven years old (Alexnet was published in 2012). There was lots of research into object detection before deep learning became usable, mostly based around feature engineering (keypoints, deformable parts, hog classifiers, etc).

Fundamentally the shift is that we've gone from handmade features developed over years of research to simply letting the model itself learn what's important. It would be nice to set the scene to realise just how transformative deep learning has been.