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Visual-Semantic Embedding Model Informed by Structured Knowledge by Jayathilaka, Mirantha; Mu, Tingting; Sattler, Uli is a scholarly article available to read on EtoBox.

What is Visual-Semantic Embedding Model Informed by Structured Knowledge about?

We propose a novel approach to improve a visual-semantic embedding model by incorporating concept representations captured from an external structured knowledge base. We investigate its performance on image classification under both standard and zero-shot settings. We propose two novel evaluation frameworks to analyse classification errors with respect to the class hierarchy indicated by the knowledge base. The approach is tested using the ILSVRC 2012 image dataset and a WordNet knowledge base. With respect to both standard and zero-shot image classification, our approach shows superior performance compared with the original approach, which uses word embeddings.

Author

Jayathilaka, Mirantha; Mu, Tingting; Sattler, Uli

Published

2020

Language

EN