Towards Real-Time Vehicle Detection on Edge Devices with Nvidia Jetson TX2

With the development of deep convolutional networks, significant advances in object detection task have been achieved. However, for applications in autonomous vehicles, it is necessary to have an efficient object detector that can process rapidly while maintaining high accuracy. This study presents our implementation and performance evaluation of two object detectors EfficientDet-Lite and Yolov3-tiny on Nvidia Jetson TX2 mobile embedded platform. Our experimental results on the KITTI dataset demonstrate that it is possible to achieve real-time and highly accurate object detection on edge devices with constrained resources.