FFMv2
Feature Fusion Module v2
**Feature Fusion Module v2** is a feature fusion module from the [M2Det](https://paperswithcode.com/method/m2det) object detection model, and is crucial for constructing the final multi-level feature pyramid. They use [1x1 convolution](https://paperswithcode.com/method/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](https://paperswithcode.com/method/tum) (TUM) – these two are of the same scale – as input, and produces the fused feature for the next TUM.
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
https://paperswithcode.com/paper/m2det-a-single-shot-object-detector-based-on
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network