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 …

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. In this paper …

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 use of …

We propose a data-centric pipeline able to generate exogenous observation data for the
New Fashion Product Performance Forecasting (NFPPF) problem, ie, predicting the …

The online fashion industry is growing fast and with it, the need for advanced systems able
to automatically solve different tasks in an accurate way. With the rapid advance of digital …

Element-based textures are a kind of texture formed by nameable elements, the texels [1],
distributed according to specific statistical distributions; it is of primary importance in many …

Capturing the essence of a textile image in a robust way is important to retrieve it in a large
repository, especially if it has been acquired in the wild (by taking a photo of the textile of …

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 business …

We present SIMCO, a completely agnostic multiclass object counting approach. SIMCO starts
by detecting foreground objects through a novel Mask RCNN-based architecture trained …

This position paper discusses the definition and implementation of Web-Physical (WP) user
profiles, which allow the creation of personalized recommendations and innovative …