2 code implementations • 21 Mar 2024 • Alberto Baldrati, Davide Morelli, Marcella Cornia, Marco Bertini, Rita Cucchiara
Fashion illustration is a crucial medium for designers to convey their creative vision and transform design concepts into tangible representations that showcase the interplay between clothing and the human body.
1 code implementation • 11 Sep 2023 • Giuseppe Cartella, Alberto Baldrati, Davide Morelli, Marcella Cornia, Marco Bertini, Rita Cucchiara
The inexorable growth of online shopping and e-commerce demands scalable and robust machine learning-based solutions to accommodate customer requirements.
1 code implementation • 22 May 2023 • Davide Morelli, Alberto Baldrati, Giuseppe Cartella, Marcella Cornia, Marco Bertini, Rita Cucchiara
In this context, image-based virtual try-on, which consists in generating a novel image of a target model wearing a given in-shop garment, has yet to capitalize on the potential of these powerful generative solutions.
1 code implementation • ICCV 2023 • Alberto Baldrati, Davide Morelli, Giuseppe Cartella, Marcella Cornia, Marco Bertini, Rita Cucchiara
Given the lack of existing datasets suitable for the task, we also extend two existing fashion datasets, namely Dress Code and VITON-HD, with multimodal annotations collected in a semi-automatic manner.
1 code implementation • 2 Apr 2023 • Roberto Amoroso, Davide Morelli, Marcella Cornia, Lorenzo Baraldi, Alberto del Bimbo, Rita Cucchiara
Recent advancements in diffusion models have enabled the generation of realistic deepfakes by writing textual prompts in natural language.
1 code implementation • 18 Apr 2022 • Davide Morelli, Matteo Fincato, Marcella Cornia, Federico Landi, Fabio Cesari, Rita Cucchiara
Dress Code is more than 3x larger than publicly available datasets for image-based virtual try-on and features high-resolution paired images (1024x768) with front-view, full-body reference models.
Ranked #5 on Virtual Try-on on VITON
no code implementations • 20 Apr 2021 • Nikola Dolezalova, Massimo Cairo, Alex Despotovic, Adam T. C. Booth, Angus B. Reed, Davide Morelli, David Plans
We developed a predictive 10-year type 2 diabetes risk score using 301 features derived from 472, 830 participants in the UK Biobank dataset while excluding any features which are not easily obtainable by a smartphone.
no code implementations • 20 Apr 2021 • Nikola Dolezalova, Angus B. Reed, Alex Despotovic, Bernard Dillon Obika, Davide Morelli, Mert Aral, David Plans
Both CPH and DeepSurv were superior in determining the CVD risk compared to Framingham score.
1 code implementation • 7 May 2017 • Davide Bacciu, Francesco Crecchi, Davide Morelli
The paper presents a novel, principled approach to train recurrent neural networks from the Reservoir Computing family that are robust to missing part of the input features at prediction time.