Search Results for author: Loic Landrieu

Found 10 papers, 8 papers with code

Scalable Surface Reconstruction with Delaunay-Graph Neural Networks

no code implementations13 Jul 2021 Raphael Sulzer, Loic Landrieu, Renaud Marlet, Bruno Vallet

We introduce a novel learning-based, visibility-aware, surface reconstruction method for large-scale, defect-laden point clouds.

Torch-Points3D: A Modular Multi-Task Frameworkfor Reproducible Deep Learning on 3D Point Clouds

2 code implementations9 Oct 2020 Thomas Chaton, Nicolas Chaulet, Sofiane Horache, Loic Landrieu

We introduce Torch-Points3D, an open-source framework designed to facilitate the use of deep networks on3D data.

Leveraging Class Hierarchies with Metric-Guided Prototype Learning

1 code implementation6 Jul 2020 Vivien Sainte Fare Garnot, Loic Landrieu

In the case of classification tasks, the severity of errors can be summarized under the form of a cost matrix, which assesses the gravity of confusing each pair of classes.

Classification General Classification +4

Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series

1 code implementation1 Jul 2020 Vivien Sainte Fare Garnot, Loic Landrieu

The increasing accessibility and precision of Earth observation satellite data offers considerable opportunities for industrial and state actors alike.

Time Series Time Series Classification

Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention

2 code implementations CVPR 2020 Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano, Nesrine Chehata

Satellite image time series, bolstered by their growing availability, are at the forefront of an extensive effort towards automated Earth monitoring by international institutions.

General Classification Time Series +1

Supervized Segmentation with Graph-Structured Deep Metric Learning

1 code implementation10 May 2019 Loic Landrieu, Mohamed Boussaha

We introduce the graph-structured contrastive loss, a loss function structured by a ground truth segmentation.

Metric Learning

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

2 code implementations CVPR 2018 Loic Landrieu, Martin Simonovsky

We propose a novel deep learning-based framework to tackle the challenge of semantic segmentation of large-scale point clouds of millions of points.

3D Semantic Segmentation

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