Generative Adversarial Network-based Visual Similarity Recommendation

Abstract

The purpose of a content-based recommendation system is to rank a set of results by how closely they match the user’s query. These days, virtually every online marketplace has some kind of recommendation system in place to steer customers to more goods and services they might enjoy. In this piece, we’ll go through how we used Generative Adversarial Networks to build an image retrieval system for e-commerce sites, with a focus on locating the best possible shoe photos to go along with a given product image. The writers of this paper conducted the study presented here. We demonstrate the outcomes of our study of the proposed deep learning network’s performance on a benchmark dataset, and we compare the network’s results to those of state-of-the-art systems.