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POP: Mining POtential Performance of new fashion products via webly
  cross-modal query expansion

POP: Mining POtential Performance of new fashion products via webly cross-modal query expansion

22 July 2022
Christian Joppi
Geri Skenderi
Marco Cristani
ArXivPDFHTML

Papers citing "POP: Mining POtential Performance of new fashion products via webly cross-modal query expansion"

4 / 4 papers shown
Title
MDiFF: Exploiting Multimodal Score-based Diffusion Models for New
  Fashion Product Performance Forecasting
MDiFF: Exploiting Multimodal Score-based Diffusion Models for New Fashion Product Performance Forecasting
Andrea Avogaro
Luigi Capogrosso
Franco Fummi
Marco Cristani
DiffM
94
0
0
07 Dec 2024
On the use of learning-based forecasting methods for ameliorating
  fashion business processes: A position paper
On the use of learning-based forecasting methods for ameliorating fashion business processes: A position paper
Geri Skenderi
Christian Joppi
Matteo Denitto
Marco Cristani
AI4TS
AI4CE
8
1
0
09 Nov 2022
A Data-Centric Approach for Training Deep Neural Networks with Less Data
A Data-Centric Approach for Training Deep Neural Networks with Less Data
Mohammad Motamedi
Nikolay Sakharnykh
T. Kaldewey
45
65
0
07 Oct 2021
Well Googled is Half Done: Multimodal Forecasting of New Fashion Product
  Sales with Image-based Google Trends
Well Googled is Half Done: Multimodal Forecasting of New Fashion Product Sales with Image-based Google Trends
Geri Skenderi
Christian Joppi
Matteo Denitto
Marco Cristani
AI4TS
6
24
0
20 Sep 2021
1