Enhanced Single-shot Detector for Small Object Detection in Remote Sensing Images

• URL: http://arxiv.org/abs/2205.05927v1
• Date: Thu, 12 May 2022 07:35:07 GMT
• Title: Enhanced Single-shot Detector for Small Object Detection in Remote Sensing Images
• Authors: Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger, Jocelyn Chanussot, Jie Yang
• Abstract summary: We propose image pyramid single-shot detector (IPSSD) for small-scale object detection. In IPSSD, single-shot detector is adopted combined with an image pyramid network to extract semantically strong features for generating candidate regions. The proposed network can enhance the small-scale features from a feature pyramid network.
• Score: 33.84369068593722
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Small-object detection is a challenging problem. In the last few years, the convolution neural networks methods have been achieved considerable progress. However, the current detectors struggle with effective features extraction for small-scale objects. To address this challenge, we propose image pyramid single-shot detector (IPSSD). In IPSSD, single-shot detector is adopted combined with an image pyramid network to extract semantically strong features for generating candidate regions. The proposed network can enhance the small-scale features from a feature pyramid network. We evaluated the performance of the proposed model on two public datasets and the results show the superior performance of our model compared to the other state-of-the-art object detectors.

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