2 citations · 2 across the 3 of their papers we have counts for
4 papers · 1 filter
On the use of learning-based forecasting methods for ameliorating fashion business processes: A position paper
Geri Skenderi, Christian Joppi, Matteo Denitto +1
The fashion industry is one of the most active and competitive markets in the world, manufacturing millions of products and reaching large audiences every year. A plethora of busin…
POP: Mining POtential Performance of new fashion products via webly cross-modal query expansion
Christian Joppi, Geri Skenderi, Marco Cristani
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…
The multi-modal universe of fast-fashion: the Visuelle 2.0 benchmark
Geri Skenderi, Christian Joppi, Matteo Denitto +2
We present Visuelle 2.0, the first dataset useful for facing diverse prediction problems that a fast-fashion company has to manage routinely. Furthermore, we demonstrate how the us…
MovingFashion: a Benchmark for the Video-to-Shop Challenge
Marco Godi, Christian Joppi, Geri Skenderi +1
Retrieving clothes which are worn in social media videos (Instagram, TikTok) is the latest frontier of e-fashion, referred to as "video-to-shop" in the computer vision literature.…