Learning to Learn from Web Data through Deep Semantic Embeddings

20 Aug 2018Raul GomezLluis GomezJaume GibertDimosthenis Karatzas

In this paper we propose to learn a multimodal image and text embedding from Web and Social Media data, aiming to leverage the semantic knowledge learnt in the text domain and transfer it to a visual model for semantic image retrieval. We demonstrate that the pipeline can learn from images with associated text without supervision and perform a thourough analysis of five different text embeddings in three different benchmarks... (read more)

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