Search Results for author: Nour Karessli

Found 6 papers, 0 papers with code

FitGAN: Fit- and Shape-Realistic Generative Adversarial Networks for Fashion

no code implementations23 Jun 2022 Sonia Pecenakova, Nour Karessli, Reza Shirvany

Through experiments on real world data at scale, we demonstrate how our approach is capable of synthesizing visually realistic and diverse fits of fashion items and explore its ability to control fit and shape of images for thousands of online garments.

Virtual Try-on

WiCV 2021: The Eighth Women In Computer Vision Workshop

no code implementations11 Mar 2022 Arushi Goel, Niveditha Kalavakonda, Nour Karessli, Tejaswi Kasarla, Kathryn Leonard, Boyi Li, Nermin Samet and, Ghada Zamzmi

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2021, organized alongside the virtual CVPR 2021.

SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce

no code implementations7 Jun 2021 Andrea Nestler, Nour Karessli, Karl Hajjar, Rodrigo Weffer, Reza Shirvany

Size and fit related returns severely impact 1. the customers experience and their dissatisfaction with online shopping, 2. the environment through an increased carbon footprint, and 3. the profitability of online fashion platforms.

WiCV 2020: The Seventh Women In Computer Vision Workshop

no code implementations11 Jan 2021 Hazel Doughty, Nour Karessli, Kathryn Leonard, Boyi Li, Carianne Martinez, Azadeh Mobasher, Arsha Nagrani, Srishti Yadav

It provides a voice to a minority (female) group in computer vision community and focuses on increasingly the visibility of these researchers, both in academia and industry.

SizeNet: Weakly Supervised Learning of Visual Size and Fit in Fashion Images

no code implementations28 May 2019 Nour Karessli, Romain Guigourès, Reza Shirvany

We propose to employ visual data to infer size and fit characteristics of fashion articles.

Gaze Embeddings for Zero-Shot Image Classification

no code implementations CVPR 2017 Nour Karessli, Zeynep Akata, Bernt Schiele, Andreas Bulling

Zero-shot image classification using auxiliary information, such as attributes describing discriminative object properties, requires time-consuming annotation by domain experts.

Classification Fine-Grained Image Classification +2

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