• S Aishwarya Rao
• Rajeev Kumar

Fashion trend forecasting is of great research significance in providing useful suggestions for both fashion companies and fashion lovers. Although various studies have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal the real complex fashion trends. We propose to forecast visual style trends before they occur. We introduce the first approach to predict the future popularity of styles discovered from fashion images in an unsupervised manner. Using these styles as a basis, we train a forecasting model to represent their trends over time. The resulting model can hypothesize new mixtures of styles that will become popular in the future, discover style dynamics (trendy vs. classic), and name the key visual attributes that will dominate tomorrow’s fashion. We demonstrate our idea applied to three datasets encapsulating 80,000 fashion products sold across six years on Amazon. Results indicate that fashion forecasting benefits greatly from visual analysis, much more than textual or meta-data cues surrounding products.

Fast fashion, Visual style, Fashion Forecasting, Style prediction, Trend analysis, Fashion dataset

"FASHION FORWARD: FORECASTING VISUAL STYLE IN FASHION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 12, page no.c362-c369, December-2022, Available :http://www.jetir.org/papers/JETIR2212254.pdf

"FASHION FORWARD: FORECASTING VISUAL STYLE IN FASHION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 12, page no. ppc362-c369, December-2022, Available at : http://www.jetir.org/papers/JETIR2212254.pdf