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 …

Jul 9, 2020 · FPN is a relatively simpler if you understand all the prerequisites well. Image pyramids (multiple images of multiple scales) are often used at the time of predictions to …

Oct 9, 2024 · At their core, FPNs are a type of neural network architecture designed to tackle one of the biggest hurdles in computer vision — handling objects at different scales. Whether …

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 …

Feb 6, 2023 · Feature Pyramid Network exploit the inherent multi-scale, pyramidal hierarchy of deep convolutional networks to construct feature pyramids with marginal extra cost. A topdown …

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection Abstract: Current state-of-the-art convolutional architectures for object detection are manually designed. Here …

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 …

In this paper, we begin by first analyzing the design defects of feature pyramid in FPN, and then introduce a new feature pyramid architec-ture named AugFPN to address these problems. …

In this paper, we present a novel dynamic feature fusion method based on the graph convolution network (GCN), called DG-FPN. The proposed GCN-based method can dynamically transfer …

In this paper, we begin by first analyzing the design defects of feature pyramid in FPN, and then introduce a new feature pyramid architecture named AugFPN to address these problems. …