Raoul de Charette

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Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation

Domain adaptation is an important task to enable learning when labels ar...
01/18/2021 ∙ by Maximilian Jaritz, et al. ∙ 11 ∙ share

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Rain rendering for evaluating and improving robustness to bad weather

Rain fills the atmosphere with water particles, which breaks the common ...
09/06/2020 ∙ by Maxime Tremblay, et al. ∙ 14 ∙ share

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LMSCNet: Lightweight Multiscale 3D Semantic Completion

We introduce a new approach for multiscale 3D semantic scene completion ...
08/24/2020 ∙ by Luis Roldao, et al. ∙ 0 ∙ share

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RGB-D-E: Event Camera Calibration for Fast 6-DOF Object Tracking

Augmented reality devices require multiple sensors to perform various ta...
06/09/2020 ∙ by Etienne Dubeau, et al. ∙ 0 ∙ share

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Model-based disentanglement of lens occlusions

With lens occlusions, naive image-to-image networks fail to learn an acc...
04/02/2020 ∙ by Fabio Pizzati, et al. ∙ 0 ∙ share

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xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

Unsupervised Domain Adaptation (UDA) is crucial to tackle the lack of an...
11/28/2019 ∙ by Maximilian Jaritz, et al. ∙ 0 ∙ share

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Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation

Image-to-image translation architectures may have limited effectiveness ...
10/23/2019 ∙ by Fabio Pizzati, et al. ∙ 18 ∙ share

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Physics-Based Rendering for Improving Robustness to Rain

To improve the robustness to rain, we present a physically-based rain re...
08/27/2019 ∙ by Shirsendu Sukanta Halder, et al. ∙ 9 ∙ share

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3D Reconstruction of Deformable Revolving Object under Heavy Hand Interaction

We reconstruct 3D deformable object through time, in the context of a li...
08/05/2019 ∙ by Raoul de Charette, et al. ∙ 3 ∙ share

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3D Surface Reconstruction from Voxel-based Lidar Data

To achieve fully autonomous navigation, vehicles need to compute an accu...
06/25/2019 ∙ by Luis Roldao, et al. ∙ 5 ∙ share

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Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation

Convolutional neural networks are designed for dense data, but vision da...
08/02/2018 ∙ by Maximilian Jaritz, et al. ∙ 4 ∙ share

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A Statistical Update of Grid Representations from Range Sensors

In a wide range of robotic applications, being able to create a 3D model...
07/23/2018 ∙ by Luis Roldao, et al. ∙ 0 ∙ share

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End-to-End Race Driving with Deep Reinforcement Learning

We present research using the latest reinforcement learning algorithm fo...
07/06/2018 ∙ by Maximilian Jaritz, et al. ∙ 0 ∙ share

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Raoul de Charette

Featured Co-authors

Patrick Pérez

Jean-François Lalonde

Tuan-Hung Vu

Emilie Wirbel

Shirsendu Sukanta Halder

Mathieu Garon

Xavier Perrotton

Fawzi Nashashibi

Luis Roldao

Maximilian Jaritz

Etienne Perot

Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation

Rain rendering for evaluating and improving robustness to bad weather

LMSCNet: Lightweight Multiscale 3D Semantic Completion

RGB-D-E: Event Camera Calibration for Fast 6-DOF Object Tracking

Model-based disentanglement of lens occlusions

xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation

Physics-Based Rendering for Improving Robustness to Rain

3D Reconstruction of Deformable Revolving Object under Heavy Hand Interaction

3D Surface Reconstruction from Voxel-based Lidar Data

Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation

A Statistical Update of Grid Representations from Range Sensors

End-to-End Race Driving with Deep Reinforcement Learning