Oct 9, 2024 · FPNs create a pyramid of features that lets the network examine both high-level (bigger objects) and low-level (smaller objects) information, ensuring that no detail is left behind.

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.

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 …

Dec 9, 2016 · Using FPN in a basic Faster R-CNN system, our method achieves state-of-the-art single-model results on the COCO detection benchmark without bells and whistles, surpassing all existing single-model entries including those from the COCO 2016 challenge winners.

Sep 9, 2020 · FPN solves this problem by generating a bottom-up and a top-down feature hierarchy with lateral connections from the network’s generated features at different scales.

Jan 14, 2025 · Among these innovations, Feature Pyramid Networks (FPN) stand out as a fundamental building block that has revolutionized how we handle multi-scale feature representation in neural networks....

Feature Pyramid Network (FPN) is an architecture designed to enhance object detection by addressing scale variation challenges in images. It constructs a feature pyramid with high-level semantics, enabling the detection of objects at different scales.

Dec 20, 2019 · In this paper, we first investigate the Feature Pyramid Network (FPN) architectures and briefly categorize them into three typical fashions: top-down, bottom-up and fusing-splitting, which have their own merits for detecting small objects, …

FPN takes a single-scale image of an arbitrary input size and outputs proportionally sized feature maps at multiple levels. FPN is independent of backbone networks (ResNet is used in the paper). The construction of FPN consists of bottom-up pathway, …

In this work, we propose Attention Aggre-gation based Feature Pyramid Network (A2-FPN), to im-prove multi-scale feature learning through attention-guided feature aggregation.