Research Area:  Machine Learning
Object detection is one of the most critical and challenging tasks in computer vision. It is the process of finding objects belonging to some predefined categories and determining their location in an image or video. This paper reviews deep learning-based object detection models. The paper discusses some benchmark datasets. The performance evaluation of different detectors on different datasets based on mean Average Precision (mAP) is reviewed. Object detection is used in different fields in different forms. Applications of object detection like pedestrian detection, autonomous driving, face detection, etc., are presented. Finally, the future scope is discussed to work on new techniques for object detection.
Author(s) Name:  Biponjot Kaur ,Sarbjeet Singh
Conferrence name:  DSMLAI 21: Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence
Publisher name:  ACM
Paper Link:   https://dl.acm.org/doi/abs/10.1145/3484824.3484889