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
Datasets

Train recognition models for street scenes

ECCV 2020 Tutorial

International, City-Scale Computer Vision Benchmarking with Mapillary MegaCities

News

We will organize a tutorial at ECCV 2020 in Glasgow, entitled "International, City-Scale Computer Vision Benchmarking with Mapillary MegaCities"

February, 2020

We got 3 papers (1 oral, 2 posters) accepted at CVPR 2020!

February, 2020

We are co-organizing the Robust Vision Challenge at ECCV 2020

February, 2020

Publications

Learning Multi-Object Tracking and Segmentation from Automatic Annotations

By Lorenzo Porzi, Markus Hofinger, Idoia Ruiz, Joan Serrat, Samuel Rota Bulò, Peter Kontschieder
Conf. on Computer Vision and Pattern Recognition (CVPR) 2020 /

Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition

By Frederik Warburg, Soren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera
Conf. on Computer Vision and Pattern Recognition (CVPR) 2020 /

Modeling the Background for Incremental Learning in Semantic Segmentation

By Fabio Cermelli, Massimiliano Mancini, Samuel Rota Bulò, Elisa Ricci, Barbara Caputo
Conf. on Computer Vision and Pattern Recognition (CVPR) 2020 /

The Mapillary Traffic Sign Dataset for Detection and Classification on a Global Scale

By Christian Ertler, Jerneja Mislej, Tobias Ollmann, Lorenzo Porzi, Gerhard Neuhold, Yubin Kuang
arXiv (technical report) /

Towards Generalization Across Depth for Monocular 3D Object Detection

By Andrea Simonelli, Samuel Rota Bulò, Lorenzo Porzi, Elisa Ricci, Peter Kontschieder
arXiv (technical report) /

Disentangling Monocular 3D Object Detection

By Andrea Simonelli, Samuel Rota Bulò, Lorenzo Porzi, Manuel López-Antequera, Peter Kontschieder
International Conf. on Computer Vision (ICCV) 2019 /

Seamless Scene Segmentation

By Lorenzo Porzi, Samuel Rota Bulò, Aleksander Colovic, Peter Kontschieder
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 /

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 /

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 /

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 /

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 /