me

Michael Firman

Linkedin // Scholar

me

I am Michael Firman, a staff research scientist at Niantic, Inc., where I work on machine learning and computer vision research to help people explore the world around them.

Previously, I worked at UCL in the Vision and Graphics group as a postdoc on the Engage project, making machine learning tools accessible to scientists across different disciplines. This work was with Prof. Mike Terry at the University of Waterloo, Dr. Gabriel Brostow at UCL and Prof. Kate Jones at UCL.

My PhD was supervised by Dr. Simon Julier and Dr. Jan Boehm. During my PhD I predominantly worked on the problem of inferring a full volumetric reconstruction of a scene, given only a single depth image as input. This problem has many applications in robotics, computer graphics and augmented reality.

During the summer of 2012 I worked at the National Institute of Informatics, Tokyo, under the supervision of Prof. Akihiro Sugimoto.

I have also served as a reviewer for CVPR, ECCV, ICCV, IROS, BMVC, ICRA, IJCV, CVIU, 3DV and ISMAR. I received CVPR's `outstanding reviewer' award in 2018, 2020 and 2022.

Publications

Mohamed Sayed, Filippo Aleotti, Jamie Watson, Zawar Qureshi, Guillermo Garcia-Hernando, Gabriel J. Brostow, Sara Vicente and Michael Firman

European Conference on Computer Vision (ECCV) 2024

Jamie Watson, Filippo Aleotti, Mohamed Sayed, Zawar Qureshi, Oisin Mac Aodha, Gabriel J. Brostow, Michael Firman and Sara Vicente

Computer Vision and Patern Recognition (CVPR) 2024

Jamie Watson, Mohamed Sayed, Zawar Qureshi, Gabriel J. Brostow, Sara Vicente, Oisin Mac Aodha and Michael Firman

Computer Vision and Patern Recognition (CVPR) 2023

Silvan Weder, Guillermo Garcia-Hernando, Áron Monszpart, Marc Pollefeys, Gabriel J. Brostow, Michael Firman and Sara Vicente

Computer Vision and Patern Recognition (CVPR) 2023

Heightfields for Efficient Scene Reconstruction for AR

Jamie Watson, Sara Vicente, Oisin Mac Aodha, Clément Godard, Gabriel J. Brostow and Michael Firman

Winter Conference on Applications of Computer Vision (WACV) 2023

Jamie Watson, Sara Vicente, Oisin Mac Aodha, Clément Godard, Gabriel J. Brostow and Michael Firman

Winter Conference on Applications of Computer Vision (WACV) 2023

SimpleRecon – 3D Reconstruction without 3D Convolutions

Mohamed Sayed, John Gibson, Jamie Watson, Victor Adrian Prisacariu, Michael Firman and Clément Godard

European Conference on Computer Vision (ECCV) 2022

Mohamed Sayed, John Gibson, Jamie Watson, Victor Adrian Prisacariu, Michael Firman and Clément Godard

European Conference on Computer Vision (ECCV) 2022

Karren Yang, Michael Firman, Eric Brachmann and Clément Godard

European Conference on Computer Vision (ECCV) 2022

Jamie Watson, Oisin Mac Aodha, Victor Adrian Prisacariu, Gabriel J. Brostow and Michael Firman

Computer Vision and Pattern Recognition (CVPR) 2021

Michaël Ramamonjisoa, Michael Firman, Jamie Watson, Vincent Lepetit and Daniyar Turmukhambetov

Computer Vision and Pattern Recognition (CVPR) 2021

Colin Graber, Grace Tsai, Michael Firman, Gabriel J. Brostow and Alexander Schwing

Computer Vision and Pattern Recognition (CVPR) 2021

Learning Stereo from Single Images

Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel J. Brostow and Michael Firman

European Conference on Computer Vision (ECCV) 2020 (Oral)

Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel J. Brostow and Michael Firman

European Conference on Computer Vision (ECCV) 2020 (Oral)

Footprints and Free Space from a Single Color Image

Jamie Watson, Michael Firman, Áron Monszpart and Gabriel J. Brostow

Computer Vision and Pattern Recognition (CVPR) 2020 (Oral)

Jamie Watson, Michael Firman, Áron Monszpart and Gabriel J. Brostow

Computer Vision and Pattern Recognition (CVPR) 2020 (Oral)

Self-Supervised Monocular Depth Hints

Jamie Watson, Michael Firman, Gabriel J. Brostow and Daniyar Turmukhambetov

International Conference of Computer Vision (ICCV) 2019

Jamie Watson, Michael Firman, Gabriel J. Brostow and Daniyar Turmukhambetov

International Conference of Computer Vision (ICCV) 2019

Digging Into Self-Supervised Monocular Depth Estimation

Clément Godard, Michael Firman, Oisin Mac Aodha and Gabriel J. Brostow

International Conference of Computer Vision (ICCV) 2019

Clément Godard, Michael Firman, Oisin Mac Aodha and Gabriel J. Brostow

International Conference of Computer Vision (ICCV) 2019

DiverseNet: When One Right Answer is not Enough

Michael Firman, Neill D. F. Campbell, Lourdes Agapito and Gabriel J. Brostow

Computer Vision and Pattern Recognition (CVPR) 2018

Michael Firman, Neill D. F. Campbell, Lourdes Agapito and Gabriel J. Brostow

Computer Vision and Pattern Recognition (CVPR) 2018

Bat detective - Deep learning tools for bat acoustic signal detection

Oisin Mac Aodha, Rory Gibb, Kate E Barlow, Ella Browning, Michael Firman, Robin Freeman, Briana Harder, Libby Kinsey, Gary R Mead, Stuart E Newson, Ivan Pandourski, Stuart Parsons, Jon Russ, Abigel Szodoray-Paradi, Farkas Szodoray-Paradi, Elena Tilova, Mark Girolami, Gabriel J. Brostow and Kate E. Jones

PLoS Computational Biology 2018

Oisin Mac Aodha, Rory Gibb, Kate E Barlow, Ella Browning, Michael Firman, Robin Freeman, Briana Harder, Libby Kinsey, Gary R Mead, Stuart E Newson, Ivan Pandourski, Stuart Parsons, Jon Russ, Abigel Szodoray-Paradi, Farkas Szodoray-Paradi, Elena Tilova, Mark Girolami, Gabriel J. Brostow and Kate E. Jones

PLoS Computational Biology 2018

Thanapong Intharah, Michael Firman and Gabriel J. Brostow

CHI 2018: Late Breaking Work 2018

RGBD Datasets: Past, Present and Future

Michael Firman

CVPR Workshop on Large Scale 3D Data: Acquisition, Modelling and Analysis 2016

Michael Firman

CVPR Workshop on Large Scale 3D Data: Acquisition, Modelling and Analysis 2016

Michael Firman, Oisin Mac Aodha, Simon Julier and Gabriel J. Brostow

Computer Vision and Pattern Recognition (CVPR) 2016 (Oral)

Learning to Discover Objects in RGB-D Images Using Correlation Clustering

Michael Firman, Diego Thomas, Simon Julier and Akihiro Sugimoto

International Conference on Intelligent Robots and Systems (IROS) 2013

Michael Firman, Diego Thomas, Simon Julier and Akihiro Sugimoto

International Conference on Intelligent Robots and Systems (IROS) 2013

Michael Firman and Simon Julier

International Conference on Intelligent Robots and Systems (IROS) 2011

Talks

Augmented Reality at Niantic: Research and Applications
BMVA Symposium
2025
AR for Everyone: A Journey through Niantic's Gaming, Mapping and Creation Technology
BitKom's 'XR-Gaming & B2B-Anwendungen: Synergien und Potenziale session'
2024
Visual positioning with Niantic's Lightship platform
BitKom's 'Navigieren, positionieren und verorten mit AR & VR'
2021
Learning and Understanding Single Image Depth Estimation in the Wild
CVPR Tutorial (with Matteo Poggi, Fabio Tosi, Filippo Aleotti, Stefano Mattoccia, Clement Godard, Jamie Watson and Gabriel Brostow)
2020
Digging into Monodepth
BMVA Symposium
2019
Learning with Uncertain and Ambiguous Data
Rank Prize Symposium
2018
Learning to complete 3D scenes
The Dyson Lab, Imperial College London
2016
Automated analysis of Rhyme
Comparative Innovations Workshop, Kings College London
2013

Computer vision resources

View from Willow Garage dataset

A list of RGBD datasets

There are many great lists of computer vision datasets on the web but no dedicated source for datasets captured by Kinect or similar devices. I created this list in an attempt to remedy the situation.

2023 update: Unfortunately I am no longer maintaining this list. Please consider it a snapshot of datasets up to around 2017.

Teaching

Simon Princes book

COMPM054/COMPGI14 Machine Vision

During my PhD I was a teaching assistant on COMPM054/COMPGI14 Machine Vision. Teaching materials are available on the Moodle page.

A digital copy of Dr. Simon Prince's book 'Computer Vision: Models, Learning, and Inference', which forms a core of the syllabus, can be downloaded from www.computervisionmodels.com


Matlab and Python

UCL Graduate School courses

During my PhD I taught on (and developed material for) the UCL Graduate School's MATLAB and Python courses. These are three and five day courses introducing graduate students from across the university to the basics of the languages.