Libraries such as OpenCV and some others saw rapid inclusion in the software bundles for Smartphones, Robotic projects, and many others, to provide detection capabilities of specific objects (face, smile, and so on), and Computer Vision like benefits, though with some constraints even before the prolific adoption of CNN.

CNN-based research in this area of object detection and Instance Segmentation provided many advancements and performance enhancements to this field, not only enabling large-scale deployment of these systems but also opening avenues for many new solutions. But before we plan to jump into CNN based advancements, it will be a good idea to understand how the challenges cited in the earlier section were answered to make object detection possible in the first place (even with all the constraints), and then we will logically start our discussion about the different researchers and the application of CNN to solve other problems that still persist with the use of traditional approaches.