activity
20182021
collaborators

5 papers

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.CV2019

FisheyeDistanceNet: Self-Supervised Scale-Aware Distance Estimation using Monocular Fisheye Camera for Autonomous Driving

Varun Ravi Kumar, Sandesh Athni Hiremath, Stefan Milz +4

Fisheye cameras are commonly used in applications like autonomous driving and surveillance to provide a large field of view (). However, they come at the cost of stro…

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…