Deep learning and computer vision

Mapillary Research is innovating the science behind the world’s leading street‑level imagery platform for understanding places.

About Mapillary Research

Welcome to Mapillary Research, a place where we share scientific papers, data, code, and news! Research at Mapillary covers machine learning using deep learning and computer vision. Two of our main directions are large-scale structure-from-motion and object recognition. These are the fundamental building blocks that power Mapillary and our processing services.

Research and product development are tightly coupled at Mapillary and our results rapidly find their way into production. We publish papers and open source code to share our findings.

Learn more about our team and open positions.

Mapillary Research Team

Meet the people behind the science

Mapillary Vistas Dataset

Diverse training data for segmentation algorithms

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Mapillary Vistas
test server

Test your results on instance- & panoptic-segmentation tasks.

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News

There will be another Joint COCO and Mapillary Workshop + Challenge at ICCV 2019

April, 2019

4 papers accepted for publication at CVPR 2019 (1 oral, 3 posters)

April, 2019

Publications

Seamless Scene Segmentation

By Lorenzo Porzi, Samuel Rota Bulò, Aleksander Colovic, Peter Kontschieder
Conf. on Computer Vision and Pattern Recognition (CVPR) 2019 /

AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs

By Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci
Conf. on Computer Vision and Pattern Recognition (CVPR) 2019 /

Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss

By Subhankar Roy, Aliaksandr Siarohin, Enver Sangineto, Samuel Rota Bulò, Nicu Sebe, Elisa Ricci
Conf. on Computer Vision and Pattern Recognition (CVPR) 2019 /

Deep Single Image Camera Calibration with Radial Distortion

By Manuel López-Antequera, Roger Marı́, Pau Gargallo, Yubin Kuang, Javier Gonzalez-Jimenez, Gloria Haro
Conf. on Computer Vision and Pattern Recognition (CVPR) 2019 /

In-Place Activated BatchNorm for Memory-Optimized Training of DNNs

By Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder
Conf. on Computer Vision and Pattern Recognition (CVPR) 2018 /

Boosting Domain Adaptation by Discovering Latent Domains

By Massimilano Mancini, Lorenzo Porzi, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci
Conf. on Computer Vision and Pattern Recognition (CVPR) 2018 /

Geometry-Aware Network for Non-Rigid Shape Prediction from a Single View

By Albert Pumarola, Antonio Agudo, Lorenzo Porzi, Alberto Sanfeliu, Vincent Lepetit, Francesc Moreno-Noguer
Conf. on Computer Vision and Pattern Recognition (CVPR) 2018 /

AutoDIAL: Automatic DomaIn Alignment Layers

By Fabio Maria Carlucci, Lorenzo Porzi, Barbara Caputo, Elisa Ricci, Samuel Rota Bulò
International Conf. on Computer Vision (ICCV) 2017 /

The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes

By Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulò, Peter Kontschieder
International Conf. on Computer Vision (ICCV) 2017 /

Loss Max-Pooling for Semantic Image Segmentation

By Samuel Rota Bulò, Gerhard Neuhold, Peter Kontschieder
Conf. on Computer Vision and Pattern Recognition (CVPR) 2017 /

Online Learning with Bayesian Classification Trees

By Samuel Rota Bulò, Peter Kontschieder
Conf. on Computer Vision and Pattern Recognition (CVPR) 2016 /

Dropout Distillation

By Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder
Intern. Conf. on Machine Learning (ICML) 2016 /