Oisin Mac Aodha

My name is Oisin Mac Aodha (how to pronounce my name) and I am a Lecturer (aka Assistant Professor) in Machine Learning in the School of Informatics at the University of Edinburgh (UoE). I am also a Turing Fellow and ELLIS Scholar. My current research interests are in the areas of computer vision and machine learning, with a specific emphasis on human-in-the-loop methods such as machine teaching.

From 2016-2019 I was fortunate to be a postdoc in Prof. Pietro Perona's Computational Vision Lab at Caltech working with the Visipedia team. Previous to Caltech, I spent three great years (2013-2016) as a postdoc in the Department of Computer Science at University College London (UCL) with Prof. Gabriel Brostow and Prof. Kate Jones. There I worked on interactive machine learning, where our goal was to design algorithms to enable non-programming scientists to semi-automatically explore events of interest in vast quantities of audio and visual data.

I did both my MSc (with Dr. Simon Prince) and PhD (with Prof. Gabriel Brostow) at UCL and have an undergraduate degree in electronic engineering from NUI Galway in Ireland. Before my PhD, I was a research assistant for one year in Prof. Marc Pollefeys' group at ETH Zurich.

Email: oisin (dot) macaodha (at) ed.ac.uk
Twitter: @oisinmacaodha
Office: Informatics Forum 2.24A



Jun 2022: I'll be speaking at the 25th BMVA Computer Vision Summer School in July and the CV4Ecology Summer School in August.
Apr 2022: I'll be an Area Chair for NeurIPS 2022.
Mar 2022: Open postdoc position in AI for biodiversity monitoring at the University of Edinburgh. More info here.
Feb 2022: I'll be an Area Chair for ECCV 2022.
Jan 2022: Co-organizing FGVC9 workshop at CVPR 2022.
Dec 2021: Open postdoc in position human-in-the-loop AI at the University of Edinburgh. More info here.
Sep 2021: Selected as a Turing Fellow and ELLIS Scholar.
May 2021: I'll be an Area Chair for BMVC 2021.
Mar 2021: FGVC8 will be held on June 25th 2021. More info here.
Mar 2021: I'll be an Area Chair for NeurIPS 2021.
Click here to read older news.
Dec 2020: Co-organizing FGVC8 workshop at CVPR 2021.
Sep 2020: I'll be an Area Chair for ICLR 2021.
Aug 2020: I'll be a Senior Program Committee Member for AAAI 2021.
Jul 2020: Presenting at the AI for Social Good workshop. Video of the talk is here.
Jul 2020: Giving a talk at the Optimizing Human Learning workshop. Video of the talk is here.
Jun 2020: You can find the videos of the talks from our FGVC7 workshop here.
May 2020: I'll be an Area Chair for NeurIPS 2020.
Mar 2020: Serving as a Program Chair for BMVC 2020. Consider submitting!
Dec 2019: Co-organizing FGVC7 workshop at CVPR 2020.
Nov 2019: Vacancies: Several openings for PhD students - see here for more details.
Oct 2019: Just started as a Lecturer (aka Assistant Professor) in Machine Learning at the University of Edinburgh.
Jul 2019: Serving on the Program Committee for Workshop on Computer Vision for Wildlife Conservation at ICCV 2019. Consider submitting your papers!
Jun 2019: Serving as an Area Chair for WACV 2020.
May 2019: Code released for our Monodepth2 paper.
Apr 2019: FGVC6 competitions now live on Kaggle.
Jan 2019: Co-organizing FGVC6 workshop at CVPR 2019.
Sep 2018: Serving as an Area Chair for ACCV 2018.
Jul 2018: Check out Niantic's occlusion demo using our monocular depth work.
Jun 2018: FGVC5 held at CVPR 2018.
Feb 2018: Launched iNaturalist 2018 challenge.
Jan 2018: Gave a talk to LA school children about the importance of bats.
Jan 2018: Co-organizing FGVC5 workshop at CVPR 2018.
Aug 2017: Read about the iNaturalist Challenge 2017 that we ran in conjunction with Caltech, iNaturalist, Cornell, Google, and Kaggle.
Jul 2017: Helped organize the Fourth Fine-Grained Visual Categorization workshop at CPVR this summer.
Jul 2017: Read about our monocular depth estimation project at UCL and The Engineer.
Jun 2017: Live deployment of our bat detection system in the former Olympic Park in London. Read about it on the BBC or follow our twitter page to get daily updates.
Sep 2016: Interviewed by SVT for our work on using machine learning to detect bats.
Aug 2016: Read about our handwriting synthesis project at the BBC, UCL, Engadget, Reuters, Gizmodo, and The Irish Times.
Jul 2016: Moved to Caltech to do a postdoc.
Mar 2016: Gave a talk about Bat Detective at UCL's Grant Museum.
Apr 2015: Blog about bat call detection over at Methods in Ecology and Evolution.


More details on Google Scholar.

Demystifying Unsupervised Semantic Correspondence Estimation
asym_eccv2022 Mehmet Aygün and Oisin Mac Aodha
ECCV 2022
[paper] [webpage] [code]
Visual Knowledge Tracing
vkt_eccv2022 Neehar Kondapaneni, Pietro Perona, and Oisin Mac Aodha
ECCV 2022
[paper] [code/data]
On Label Granularity and Object Localization
inatloc500_eccv2022 Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge Belongie, Andrew Howard, and Oisin Mac Aodha
ECCV 2022
[paper] [code/data]
Exploring Fine-grained Audiovisual Categorization with the SSW60 Dataset
ssw60_eccv2022 Grant Van Horn*, Rui Qian*, Kimberly Wilber, Hartwig Adam, Oisin Mac Aodha, and Serge Belongie
ECCV 2022
[paper] [code/data]
When Does Contrastive Visual Representation Learning Work?
when_self_supp Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, and Serge Belongie
CVPR 2022
[paper] [webpage] [video]
Fine-Grained Image Analysis with Deep Learning: A Survey
fgvc_survey Xiu-Shen Wei, Yi-Zhe Song, Oisin Mac Aodha, Jianxin Wu, Yuxin Peng, Jinhui Tang, Jian Yang, and Serge Belongie
PAMI 2021
Shazam for Bats: Internet of Things for Continuous Real-Time Biodiversity Monitoring
shazam_bats Sarah Gallacher, Duncan Wilson, Alison Fairbrass, Daniyar Turmukhambetov, Michael Firman, Stefan Kreitmayer, Oisin Mac Aodha, Gabriel Brostow, and Kate Jones
IET Smart Cities 2021
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring
focus_pos Omiros Pantazis, Gabriel Brostow, Kate Jones, and Oisin Mac Aodha
ICCV 2021
[paper] [code] [video]
ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation
view_net Octave Mariotti, Oisin Mac Aodha, and Hakan Bilen
ICCV 2021
Benchmarking Representation Learning for Natural World Image Collections
NeWT Grant Van Horn, Elijah Cole, Sara Beery, Kimberly Wilber, Serge Belongie, and Oisin Mac Aodha
CVPR 2021 (Oral)
[paper] [code/data] [video]
Multi-Label Learning From Single Positive Labels
ROLE Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, and Nebojsa Jojic
CVPR 2021
[paper] [video] [code]
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth
ManyDepth Jamie Watson, Oisin Mac Aodha, Victor Prisacariu, Gabriel Brostow, and Michael Firman
CVPR 2021
[paper] [code]
Learning Stereo from Single Images
Single Stereo Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel Brostow, and Michael Firman
ECCV 2020 (Oral)
[paper] [code]
Geocoding of Trees From Street Addresses and Street-Level Images
StreetTrees Daniel Laumer, Nico Lang, Natalie van Doorn, Oisin Mac Aodha, Pietro Perona, and Jan Dirk Wegner
Journal of Photogrammetry and Remote Sensing 2020
[paper] [arxiv]
Teaching Multiple Concepts to a Forgetful Learner
Forgetful Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, and Adish Singla
NeurIPS 2019
Presence-Only Geographical Priors for Fine-Grained Image Classification
Geo Priors Oisin Mac Aodha, Elijah Cole, and Pietro Perona
ICCV 2019
[paper] [code] [video] [webpage]
Digging Into Self-Supervised Monocular Depth Estimation
Monodepth 2.0 Clement Godard, Oisin Mac Aodha, Michael Firman, and Gabriel Brostow
ICCV 2019
[paper] [video] [code]
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners
Adaptive 2018 Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, and Yisong Yue
NeurIPS 2018
It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data
Rel Pose Matteo Ruggero Ronchi, Oisin Mac Aodha, Robert Eng, and Pietro Perona
BMVC 2018 (Oral)
[paper] [webpage] [code] [video]
Teaching Categories to Human Learners with Visual Explanations
Teach CVPR 2018 Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, and Yisong Yue
CVPR 2018 (Spotlight)
[paper] [code] [video]
Context Embedding Networks
CEN Kun ho Kim, Oisin Mac Aodha, and Pietro Perona
CVPR 2018 (Spotlight)
The iNaturalist Species Classification and Detection Dataset
iNat 2017 Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie
CVPR 2018 (Spotlight)
[paper] [webpage] [video]
Bat Detective - Deep Learning Tools for Bat Acoustic Signal Detection
Bat Detective Oisin Mac Aodha, Rory Gibb, Kate Barlow, Ella Browning, Michael Firman, Robin Freeman, Briana Harder, Libby Kinsey, Gary Mead, Stuart 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 [paper] [webpage]
Near-Optimal Machine Teaching via Explanatory Teaching Sets
AIStats 2018 Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, and Yisong Yue
Interpretable Machine Teaching via Feature Feedback
NIPS WS 2017 Shihan Su, Yuxin Chen, Oisin Mac Aodha, Pietro Perona, and Yisong Yue
NeurIPS Workshop Teaching Machines, Robots, and Humans 2017
Unsupervised Monocular Depth Estimation with Left-Right Consistency
CVPR 2017 Clement Godard, Oisin Mac Aodha, and Gabriel J. Brostow
CVPR 2017 (Oral)
[paper] [code] [webpage]
Structured Prediction of Unobserved Voxels From a Single Depth Image
CVPR 2016 Michael Firman, Oisin Mac Aodha, Simon Julier, and Gabriel J. Brostow
CVPR 2016 (Oral)
[paper] [webpage]
My text in Your Handwriting
ToG 2016 Tom S.F. Haines, Oisin Mac Aodha, and Gabriel J. Brostow
Transactions on Graphics (SIGGRAPH) 2016
[paper] [code] [webpage]
Becoming the Expert - Interactive Multi-Class Machine Teaching
CVPR 2015 Edward Johns, Oisin Mac Aodha, and Gabriel J. Brostow
CVPR 2015 (Oral)
[paper] [webpage]
Putting the Scientist in the Loop - Accelerating Scientific Progress with Interactive Machine Learning
ICPR 2014 Oisin Mac Aodha, Vassilios Stathopoulos, Michael Terry, Kate E. Jones, Gabriel J. Brostow, and Mark Girolami
ICPR 2014
Hierarchical Subquery Evaluation for Active Learning on a Graph
CVPR 2014 Oisin Mac Aodha, Neill D.F. Campbell, Jan Kautz, and Gabriel J. Brostow
CVPR 2014 (Oral)
[paper] [webpage]
Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees
ICCV 2013 Oisin Mac Aodha and Gabriel J. Brostow
ICCV 2013
[paper] [webpage]
Learning a Confidence Measure for Optical Flow
PAMI 2013 Oisin Mac Aodha, Ahmad Humayun, Marc Pollefeys, and Gabriel J. Brostow
PAMI 2013
[paper] [webpage]
Patch Based Synthesis for Single Depth Image Super-Resolution
ECCV 2012 Oisin Mac Aodha, Neill D.F. Campbell, Arun Nair, and Gabriel J. Brostow
ECCV 2012
[paper] [webpage]
Learning to Find Occlusion Regions
CVPR 2011 Ahmad Humayun, Oisin Mac Aodha, and Gabriel J. Brostow
CVPR 2011
[paper] [webpage]
Segmenting Video Into Classes of Algorithm-Suitability
CVPR 2010 Oisin Mac Aodha, Gabriel J Brostow, and Marc Pollefeys
CVPR 2010
[paper] [webpage]
Evolving Plastic Responses in Artificial Cell Models
Cell Im John Maher, Fearghal Morgan, and Oisin Mac Aodha
Congress on Evolutionary Computation 2009


Bingchen Zhao, PhD at UoE - starting Oct 2022
Yanran Li, Postdoc at UoE - started Jul 2022
Mehmet Aygün, PhD at UoE - started Sep 2021
Santiago Martínez Balvanera, PhD at UCL with Prof. Kate Jones - started Jan 2021
Omiros Pantazis, PhD at UCL with Prof. Kate Jones - started Apr 2020

More information about the larger Vision at Edinburgh group can be found here.