Working Paper Article Version 1 This version is not peer-reviewed

EFN: Field-based Object Detection for Aerial Images

Version 1 : Received: 12 September 2020 / Approved: 14 September 2020 / Online: 14 September 2020 (00:14:31 CEST)

How to cite: Liu, J.; Zheng, H. EFN: Field-based Object Detection for Aerial Images. Preprints 2020, 2020090310 Liu, J.; Zheng, H. EFN: Field-based Object Detection for Aerial Images. Preprints 2020, 2020090310

Abstract

In this paper, We propose a field-based network for object detection: Ellipse Field Network(EFN). It is a elegant way to detect the objects that is cluttered and rotated. EFN works with the probability fields which can preserves the information of object distribution in image space during forward propagation. It is for object detection in aerial images, and also work well in natural images detection. For an input image, The extensive experiments have validated that EFN can work with a light weight model and doesn’t sacrificing performance. We achieve state-of-the-art results in aerial images test, and a good score in natural images.

Subject Areas

Aerial Image; Object detection; Semantic segmentation; Probability field

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