A drone detector with modified backbone and multiple pyramid featuremaps enhancement structure (MDDPE)

TL;DR

This paper introduces MDDPE, a drone detection model with a modified backbone and enhanced feature maps, utilizing novel modules and anchor matching techniques to improve detection accuracy in real scenarios.

Contribution

The paper proposes a new drone detection architecture with enhanced feature map modules and improved anchor matching, advancing detection robustness and accuracy.

Findings

MDDPE outperforms existing detectors on drone benchmarks.

Enhanced feature modules improve detection robustness.

Updated anchor matching increases localization accuracy.

Abstract

This work presents a drone detector with modified backbone and multiple pyramid feature maps enhancement structure (MDDPE). Novel feature maps improve modules that uses different levels of information to produce more robust and discriminatory features is proposed. These module includes the feature maps supplement function and the feature maps recombination enhancement function.To effectively handle the drone characteristics, auxiliary supervisions that are implemented in the early stages by employing tailored anchors designed are utilized. To further improve the modeling of real drone detection scenarios and initialization of the regressor, an updated anchor matching technique is introduced to match anchors and ground truth drone as closely as feasible. To show the proposed MDDPE's superiority over the most advanced detectors, extensive experiments are carried out using well-known drone detection benchmarks.