Latent Embeddings for Zero-shot Classification

CVPR 2016 Yongqin XianZeynep AkataGaurav SharmaQuynh NguyenMatthias HeinBernt Schiele

We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero-shot classification. The proposed method augments the state-of-the-art bilinear compatibility model by incorporating latent variables... (read more)

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