Towards Pedestrian Detection Using RetinaNet in ECCV 2018 Wider\n Pedestrian Detection Challenge

Abstract

The main essence of this paper is to investigate the performance of RetinaNet\nbased object detectors on pedestrian detection. Pedestrian detection is an\nimportant research topic as it provides a baseline for general object detection\nand has a great number of practical applications like autonomous car, robotics\nand Security camera. Though extensive research has made huge progress in\npedestrian detection, there are still many issues and open for more research\nand improvement. Recent deep learning based methods have shown state-of-the-art\nperformance in computer vision tasks such as image classification, object\ndetection, and segmentation. Wider pedestrian detection challenge aims at\nfinding improve solutions for pedestrian detection problem. In this paper, We\npropose a pedestrian detection system based on RetinaNet. Our solution has\nscored 0.4061 mAP. The code is available at\nhttps://github.com/miltonbd/ECCV_2018_pedestrian_detection_challenege.\n