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