Object Detection & Segmentation

Those working with Neural Networks know how complicated Object Detection techniques can be. It is no wonder there is no straight forward resource for training them. You are always required to convert your data to a COCO-like JSON or some other unwanted format. It is never a plug and play experience. Moreover, no diagram thoroughly explains Faster R-CNN or YOLO as there is for … [Read more...] about Why Is Object Detection So Messy?

Object detection in crowded scenes is challenging. When objects gather, they tend to overlap largely with each other, leading to occlusions. Occlusion caused by objects of the same class is called intra-class occlusion, also referred to as crowd occlusion. Object detectors need to determine the locations of different objects in the crowd and accurately delineate their … [Read more...] about Deep-Learning Based Object Detection in Crowded Scenes

Instance segmentation is a challenging computer vision task that requires the prediction of object instances and their per-pixel segmentation mask. This makes it a hybrid of semantic segmentation and object detection. Ever since Mask R-CNN was invented, the state-of-the-art method for instance segmentation has largely been Mask RCNN and its variants … [Read more...] about Single Stage Instance Segmentation – A Review

I like deep learning a lot but Object Detection is something that doesn’t come easily to me. And Object detection is important and does have its uses. Most common of them being self-driving cars, medical imaging and face detection. It is definitely a hard problem to solve. And with so many moving parts and new concepts introduced over the long history of this problem, it … [Read more...] about Demystifying Object Detection And Instance Segmentation For Data Scientists