FeatureNMS-- the rule whether to add p from P to D or not is adjusted

FeatureNMS
算法流程图
FeatureNMS-- the rule whether to add p from P to D or not is adjusted
具体改进

In any other case the two bounding boxes might belong to the same or to different objects—the intersection over union alone cannot be used to make a final decision. In this case we calculate the L2 distance of feature embeddings for both bounding boxes. If this distance is larger than a threshold T we assume that the bounding boxes belong to different objects. Otherwise they are likely to belong to the same object

用两个阈值来控制上述方框内的内容,使得对于IOU小于N2的还能根据嵌入特征进行二次筛选,如果比较p和d的嵌入特征L2距离大于一个阈值,说明他与p不是同一个类

: The proposal p with the highest confidence score in P

嵌入特征提取:

We add one head to the RetinaNet backbone. This head outputs a feature
embedding for each anchor box. We chose an embedding of length of 32,
but other lengths are possible.