Abstract:Recent advances in deep learning have enabled state-of-the-art performance in detecting medium and large-size objects. However, small object detection remains challenging primarily due to the scarcity of information. This paper proposes an end-to-end fusion network that integrates deep and hand-crafted features to address this limitation. A fusion module based on semantic context information is designed to enhance feature discrimination ability. Additionally, we introduce a kind of feature-contrast loss to inc… Show more
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