A walkthrough of the Feature Pyramid Network (FPN) paper explaining how FPN works as a 'neck' component in object detection models. Covers the evolution of multi-scale detection approaches (featurized image pyramids, pyramidal feature hierarchy, FPN), explains the top-down pathway and lateral connections that enrich shallow feature maps with semantic information from deeper layers, and provides a full PyTorch implementation from scratch including a CNN backbone, FPN neck, and RPN head assembled into a complete detection model.
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