FIGURE 1.

Overview of the proposed network. The encoder and projection head embed the input image $\mathbf{x}$ into a representation $\mathbf{r}$ . The average similarity between the representation $\mathbf{r}$ and the unit ${\mathbf{u}}_i^j$ in the class knowledge bank (CKB) C _i is measured as the logit of x for class i. The CKBs are parameterized by a matrix of dimension N × M × D, where N is the number of classes, M is the number of units in each CKB, and D denotes the dimension of a unit. The CKBs are randomly initialized and can be trained through back-propagation.