Prototypical Model with Novel Information-theoretic Loss Function for Generalized Zero Shot Learning

no code implementations • 6 Dec 2021 • Chunlin Ji, Hanchu Shen, Zhan Xiong, Feng Chen, Meiying Zhang, Huiwen Yang

Then We propose three information-theoretic loss functions for deterministic GZSL model: a mutual information loss to bridge seen data and target classes; an uncertainty-aware entropy constraint loss to prevent overfitting when using seen data to learn the embedding of target classes; a semantic preserving cross entropy loss to preserve the semantic relation when mapping the semantic representations to the common space.

Generalized Zero-Shot Learning Relation +1