FFMv2

2000년 도입 · 논문 2편에서 사용

Feature Fusion Module v2 is a feature fusion module from the M2Det object detection model, and is crucial for constructing the final multi-level feature pyramid. They use 1x1 convolution layers to compress the channels of the input features and use a concatenation operation to aggregate these feature map. FFMv2 takes the base feature and the largest output feature map of the previous Thinned U-Shape Module (TUM) – these two are of the same scale – as input, and produces the fused feature for the next TUM.

출처: M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

소개 논문: M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network