What is multi-scale feature fusion in modern detection architectures?

Multi-scale feature fusion combines features from different resolutions to improve detection of objects of varying sizes.

Objects in images vary in scale, so modern architectures fuse low-level high-resolution features with high-level semantic features. Techniques include FPN, PANet, BiFPN, and NAS-FPN. BiFPN introduces weighted feature fusion to learn optimal contribution from each scale.