In this talk, we will dive deeper into the problem of object detection. Object detection is the problem of identifying objects in an image and denote their locations using bounding boxes. We will talk about how this was done pre deep learning. Then we will talk about how this was done in a series of deep learning models proposed over the past few years.
Note: No background required, but it would help if you had attended or viewed Part 1 of the tutorial.