SAFDet : a semi-anchor-free detector for effective detection of oriented objects in aerial images

Fang, Zhenyu and Ren, Jinchang and Sun, He and Marshall, Stephen and Han, Junwei and Zhao, Huimin (2020) SAFDet : a semi-anchor-free detector for effective detection of oriented objects in aerial images. Remote Sensing, 12 (19). 3225. ISSN 2072-4292

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    Abstract

    An oriented bounding box (OBB) is preferable over a horizontal bounding box (HBB) in accurate object detection. Most of existing works utilize a two-stage detector for locating the HBB and OBB, respectively, which have suffered from the misaligned horizontal proposals and the interference from complex backgrounds. To tackle these issues, region of interest transformer and attention models were proposed, yet they are extremely computationally intensive. To this end, we propose a semi-anchor-free detector (SAFDet) for object detection in aerial images, where a rotation-anchor-free-branch (RAFB) is used to enhance the foreground features via precisely regressing the OBB. Meanwhile, a center-prediction-module (CPM) is introduced for enhancing object localization and suppressing the background noise. Both RAFB and CPM are deployed during training, avoiding increased computational cost of inference. By evaluating on DOTA and HRSC2016 datasets, the efficacy of our approach has been fully validated for a good balance between the accuracy and computational cost.

    Creators(s): Fang, Zhenyu, Ren, Jinchang ORCID logoORCID: https://orcid.org/0000-0001-6116-3194, Sun, He, Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628, Han, Junwei and Zhao, Huimin;
    Item type:Article
    ID code:74073
    Keywords:rotate region, convolutional neural network, anchor free, aerial object detection, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Technology and Innovation Centre > Sensors and Asset Management
    Strategic Research Themes > Measurement Science and Enabling Technologies
    Depositing user: Pure Administrator
    Date deposited:05 Oct 2020 08:28
    Last modified:15 Jan 2021 04:44
    URI:https://strathprints.strath.ac.uk/id/eprint/74073
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