activity
20182022
most citedA study of deep perceptual metrics for image quality assessment

6 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20226 cited

A study of deep perceptual metrics for image quality assessment

Rémi Kazmierczak, Gianni Franchi, Nacim Belkhir +2

Several metrics exist to quantify the similarity between images, but they are inefficient when it comes to measure the similarity of highly distorted images. In this work, we propo…

cs.CV2021

Does it work outside this benchmark? Introducing the Rigid Depth Constructor tool, depth validation dataset construction in rigid scenes for the masses

Clément Pinard, Antoine Manzanera

We present a protocol to construct your own depth validation dataset for navigation. This protocol, called RDC for Rigid Depth Constructor, aims at being more accessible and cheape…

cs.CV2018

Learning structure-from-motion from motion

Clément Pinard, Laure Chevalley, Antoine Manzanera +1

This work is based on a questioning of the quality metrics used by deep neural networks performing depth prediction from a single image, and then of the usability of recently publi…

cs.CV2018

Multi range Real-time depth inference from a monocular stabilized footage using a Fully Convolutional Neural Network

Clément Pinard, Laure Chevalley, Antoine Manzanera +1

Using a neural network architecture for depth map inference from monocular stabilized videos with application to UAV videos in rigid scenes, we propose a multi-range architecture f…

cs.CV2018

End-to-end depth from motion with stabilized monocular videos

Clément Pinard, Laure Chevalley, Antoine Manzanera +1

We propose a depth map inference system from monocular videos based on a novel dataset for navigation that mimics aerial footage from gimbal stabilized monocular camera in rigid sc…