Survey on Different Object Detection and Segmentation Methods


Authors : Sanket Chandrakant Patel

Volume/Issue : Volume 6 - 2021, Issue 1 - January

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/2YcqK51

Object Detection is a common problem associated closely with the Computer Vision problem which deals with identifying objects and locating exact positions of certain classes in the image. Interpreting the object positions and localization of classes can be done in various different ways, the most common ones are creating a bounding box around the object and another is marking every pixel in the image which contains the object which is called image segmentation. This survey is based on comparing the two broad classes of object detection algorithms that differ from each other in aspects of a number of stages or steps involved in performing the detection, single-stage detection(YOLO), and two-stage detection (or multi-stage detection) (CNN’s). We will also be looking at SOLO architecture which puts light on a completely different approach for segmentation.

Keywords : Object Detection, Localization, Detection, Segmentation.

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