Fast Object Detector Based on Convolutional Neural Networks

Abstract

We propose a fast object detector, based on Convolutional Neural Network (CNN). The object detector, which operates on RGB images, is designed for a mobile robot equipped with a robotic manipulator. The proposed detector is designed to quickly and accurately detect objects which are common in small manufactories and workshops. We propose a fully convolutional architecture of neural network which allows the full GPU implementation. We provide results obtained on our custom dataset based on ImageNet and other common datasets, like COCO or PascalVOC. We also compare the proposed method with other state of the art object detectors.