Web: http://arxiv.org/abs/2109.09824

Sept. 16, 2022, 1:15 a.m. | Geri Skenderi, Christian Joppi, Matteo Denitto, Marco Cristani

cs.CV updates on arXiv.org arxiv.org

New fashion product sales forecasting is a challenging problem that involves
many business dynamics and cannot be solved by classical forecasting
approaches. In this paper, we investigate the effectiveness of systematically
probing exogenous knowledge in the form of Google Trends time series and
combining it with multi-modal information related to a brand-new fashion item,
in order to effectively forecast its sales despite the lack of past data. In
particular, we propose a neural network-based approach, where an encoder learns
a …

arxiv fashion forecasting google image multimodal product sales trends

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