A causal view of compositional zero-shot recognition

Understand

People easily recognize new visual categories that are new combinations of known components.

• This compositional generalization capacity is critical for learning in real-world domains like vision and language because the long tail of new combinations dominates the distribution.
• Unfortunately, learning systems struggle with compositional generalization because they often build on features that are correlated with class labels even if they are not "essential" for the class.
• This leads to consistent misclassification of samples from a new distribution, like new combinations of known components.