Object Detection in Aerial Imagery
- URL: http://arxiv.org/abs/2211.15479v1
- Date: Tue, 15 Nov 2022 11:22:18 GMT
- Title: Object Detection in Aerial Imagery
- Authors: Dmitry Demidov, Rushali Grandhe, Salem AlMarri
- Abstract summary: We show the performance of two-stage, one-stage and attention based object detectors on the iSAID dataset.
We also show a comparative study highlighting the pros and cons of different models in aerial imagery setting.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Object detection in natural images has achieved remarkable results over the
years. However, a similar progress has not yet been observed in aerial object
detection due to several challenges, such as high resolution images, instances
scale variation, class imbalance etc. We show the performance of two-stage,
one-stage and attention based object detectors on the iSAID dataset.
Furthermore, we describe some modifications and analysis performed for
different models - a) In two stage detector: introduced weighted attention
based FPN, class balanced sampler and density prediction head. b) In one stage
detector: used weighted focal loss and introduced FPN. c) In attention based
detector: compare single,multi-scale attention and demonstrate effect of
different backbones. Finally, we show a comparative study highlighting the pros
and cons of different models in aerial imagery setting.
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