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POP: Mining POtential Performance of new fashion products via webly cross-modal query expansion. (arXiv:2207.11001v1 [cs.CV])
July 25, 2022, 1:12 a.m. | Christian Joppi, Geri Skenderi, Marco Cristani
cs.CV updates on arXiv.org arxiv.org
We propose a data-centric pipeline able to generate exogenous observation
data for the New Fashion Product Performance Forecasting (NFPPF) problem, i.e.,
predicting the performance of a brand-new clothing probe with no available past
observations. Our pipeline manufactures the missing past starting from a
single, available image of the clothing probe. It starts by expanding textual
tags associated with the image, querying related fashionable or unfashionable
images uploaded on the web at a specific time in the past. A binary classifier …
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