Applications of Generative Adversarial Models in Visual Search Reformulation

10/28/2019

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by   Kyle Xiao, et al.

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Query reformulation is the process by which a input search query is refined by the user to match documents outside the original top-n results. On average, roughly 50 suggestion tools are used 35 as text search queries are, however, such a feature has yet to be explored at scale for visual search. This is because reformulation for images presents a novel challenge to seamlessly transform visual features to match user intent within the context of a typical user session. In this paper, we present methods of semantically transforming visual queries, such as utilizing operations in the latent space of a generative adversarial model for the scenarios of fashion and product search.