DeepAI AI Chat
Log In Sign Up

Artificial and beneficial – Exploiting artificial images for aerial vehicle detection

04/07/2021
by   Immanuel Weber, et al.
0

Object detection in aerial images is an important task in environmental, economic, and infrastructure-related tasks. One of the most prominent applications is the detection of vehicles, for which deep learning approaches are increasingly used. A major challenge in such approaches is the limited amount of data that arises, for example, when more specialized and rarer vehicles such as agricultural machinery or construction vehicles are to be detected. This lack of data contrasts with the enormous data hunger of deep learning methods in general and object recognition in particular. In this article, we address this issue in the context of the detection of road vehicles in aerial images. To overcome the lack of annotated data, we propose a generative approach that generates top-down images by overlaying artificial vehicles created from 2D CAD drawings on artificial or real backgrounds. Our experiments with a modified RetinaNet object detection network show that adding these images to small real-world datasets significantly improves detection performance. In cases of very limited or even no real-world images, we observe an improvement in average precision of up to 0.70 points. We address the remaining performance gap to real-world datasets by analyzing the effect of the image composition of background and objects and give insights into the importance of background.

READ FULL TEXT

page 4

page 5

page 6

page 8

page 11

page 12

09/22/2020

PennSyn2Real: Training Object Recognition Models without Human Labeling

Scalability is a critical problem in generating training images for deep...
08/30/2021

LUAI Challenge 2021 on Learning to Understand Aerial Images

This report summarizes the results of Learning to Understand Aerial Imag...
02/12/2021

A novel method for object detection using deep learning and CAD models

Object Detection (OD) is an important computer vision problem for indust...
05/17/2021

Learning to Automatically Catch Potholes in Worldwide Road Scene Images

Among several road hazards that are present in any paved way in the worl...
02/11/2020

Improving Place Recognition Using Dynamic Object Detection

Traditional appearance-based place recognition algorithms based on handc...
07/22/2021

An overcome of far-distance limitation on tunnel CCTV-based accident detection in AI deep-learning frameworks

Tunnel CCTVs are installed to low height and long-distance interval. How...
10/28/2019

Addressing the Sim2Real Gap in Robotic 3D Object Classification

Object classification with 3D data is an essential component of any scen...