Oct 9, 2024 · FPNs work in a similar way. They create a pyramid structure of features from an image at multiple scales. The idea is simple: the network extracts information at various “heights” or...

A Feature Pyramid Network, or FPN, is a feature extractor that takes a single-scale image of an arbitrary size as input, and outputs proportionally sized feature maps at multiple levels, in a fully convolutional fashion. This process is independent of the backbone convolutional architectures.

Jul 7, 2021 · 本文介绍了Feature Pyramid Networks (FPN)在目标检测中的关键作用，它通过构建特征金字塔结构，有效应对小目标检测，提升性能并减少计算成本。 FPN结合了图像金字塔概念与深度学习网络，利用top-down和lateral连接，显著改善了Faster R-CNN的性能。 文章还展示了FPN在COCO数据集上的优秀表现和在实例分割任务中的应用潜力。

Nov 9, 2017 · A top-down architecture with lateral connections is developed for building high-level semantic feature maps at all scales. This architecture, called a Feature Pyramid Network (FPN), shows significant improvement as a generic feature extractor in several applications.

Jan 5, 2020 · Faster R-CNN⁵ detector with FPN backbone is a multi-scale detector that realizes high accuracy for detecting tiny to large objects, making itself the de-facto standard detector (see Fig. 1)....

Nov 14, 2024 · By leveraging both high- and low-level feature maps in a structured way, FPN achieves a robust multi-scale representation that significantly enhances detection accuracy. Here’s a breakdown of how...

Jun 17, 2023 · Feature pyramid network (FPN) is a typical structure in object detection. It can improve the accuracy of detection results by fusing feature information at different resolutions and enhancing the expression ability of different levels of features.

In this paper, we exploit the inherent multi-scale, pyramidal hierarchy of deep convolutional networks to con-struct feature pyramids with marginal extra cost. A top-down architecture with lateral connections is developed for building high-level semantic feature maps at all scales.

Dec 9, 2016 · A top-down architecture with lateral connections is developed for building high-level semantic feature maps at all scales. This architecture, called a Feature Pyramid Network (FPN), shows significant improvement as a generic feature extractor in several applications.

Sep 21, 2020 · In the paper, we propose more efficient dense feature pyramid network structure, which call Dense-FPN. Our architecture essentially adds a series of dense skip pathways for FPN.