34 citations · 73 across the 5 of their papers we have counts for
14 papers
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study
Javiera Castillo-Navarro, Bertrand Le Saux, Alexandre Boulch +2
The development of semi-supervised learning techniques is essential to enhance the generalization capacities of machine learning algorithms. Indeed, raw image data are abundant whi…
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport
Gilles Puy, Alexandre Boulch, Renaud Marlet
We propose and study a method called FLOT that estimates scene flow on point clouds. We start the design of FLOT by noticing that scene flow estimation on point clouds reduces to e…
STaRFlow: A SpatioTemporal Recurrent Cell for Lightweight Multi-Frame Optical Flow Estimation
Pierre Godet, Alexandre Boulch, Aurélien Plyer +1
We present a new lightweight CNN-based algorithm for multi-frame optical flow estimation. Our solution introduces a double recurrence over spatial scale and time through repeated u…
FKAConv: Feature-Kernel Alignment for Point Cloud Convolution
Alexandre Boulch, Gilles Puy, Renaud Marlet
Recent state-of-the-art methods for point cloud processing are based on the notion of point convolution, for which several approaches have been proposed. In this paper, inspired by…
Technical Report: Co-learning of geometry and semantics for online 3D mapping
Marcela Carvalho, Maxime Ferrera, Alexandre Boulch +3
This paper is a technical report about our submission for the ECCV 2018 3DRMS Workshop Challenge on Semantic 3D Reconstruction \cite{Tylecek2018rms}. In this paper, we address 3D s…
Surface Reconstruction from 3D Line Segments
Pierre-Alain Langlois, Alexandre Boulch, Renaud Marlet
In man-made environments such as indoor scenes, when point-based 3D reconstruction fails due to the lack of texture, lines can still be detected and used to support surfaces. We pr…