687 citations · 1.1k across the 33 of their papers we have counts for
5 papers · 1 filter
Deep learning for semantic segmentation of remote sensing images with rich spectral content
A Hamida, A. Benoît, P. Lambert +4
With the rapid development of Remote Sensing acquisition techniques, there is a need to scale and improve processing tools to cope with the observed increase of both data volume an…
Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks
Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre
In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolution…
Towards seamless multi-view scene analysis from satellite to street-level
Sébastien Lefèvre, Devis Tuia, Jan Dirk Wegner +2
In this paper, we discuss and review how combined multi-view imagery from satellite to street-level can benefit scene analysis. Numerous works exist that merge information from rem…
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps
Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre
In this work, we investigate the use of OpenStreetMap data for semantic labeling of Earth Observation images. Deep neural networks have been used in the past for remote sensing dat…
Fusion of Heterogeneous Data in Convolutional Networks for Urban Semantic Labeling (Invited Paper)
Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre
In this work, we present a novel module to perform fusion of heterogeneous data using fully convolutional networks for semantic labeling. We introduce residual correction as a way…