Feature Extractors

Feature Intertwiner

Introduced by Li et al. in Feature Intertwiner for Object Detection

Feature Intertwiner is an object detection module that leverages the features from a more reliable set to help guide the feature learning of another less reliable set. The mutual learning process helps two sets to have closer distance within the cluster in each class. The intertwiner is applied on the object detection task, where a historical buffer is proposed to address the sample missing problem during one mini-batch and the optimal transport (OT) theory is introduced to enforce the similarity among the two sets.

Source: Feature Intertwiner for Object Detection


Paper Code Results Date Stars


Task Papers Share
Object Detection 1 100.00%