2 citations · 3 across the 5 of their papers we have counts for
6 papers
A Reference-Free Framework for Evaluating Single-Frame ISP Pipelines
Yujin Cho, Sira Ferradans, Jean-Michel Morel +2
Evaluating camera image signal processing (ISP) pipelines requires measuring low-level artifacts introduced by operations such as denoising, demosaicing, tone mapping, and compress…
Deep Portrait Quality Assessment. A NTIRE 2024 Challenge Survey
Nicolas Chahine, Marcos V. Conde, Daniela Carfora +4
This paper reviews the NTIRE 2024 Portrait Quality Assessment Challenge, highlighting the proposed solutions and results. This challenge aims to obtain an efficient deep neural net…
Pairwise Comparisons Are All You Need
Nicolas Chahine, Sira Ferradans, Jean Ponce
Blind image quality assessment (BIQA) approaches, while promising for automating image quality evaluation, often fall short in real-world scenarios due to their reliance on a gener…
An Image Quality Assessment Dataset for Portraits
Nicolas Chahine, Ana-Stefania Calarasanu, Davide Garcia-Civiero +3
Year after year, the demand for ever-better smartphone photos continues to grow, in particular in the domain of portrait photography. Manufacturers thus use perceptual quality crit…
Table-Of-Contents generation on contemporary documents
Najah-Imane Bentabet, Rémi Juge, Sira Ferradans
The generation of precise and detailed Table-Of-Contents (TOC) from a document is a problem of major importance for document understanding and information extraction. Despite its i…
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines
Youness Mansar, Lorenzo Gatti, Sira Ferradans +2
In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands. More specifically, our approach leverages affective lexica and word embeddi…