Oisin Mac Aodha

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 76

Top Venues

University College London, UK (PHD)

Education History

University College London, UK

PHD

Publications

Mehmet Aygün, Prithviraj Dhar, Zhicheng Yan, Oisin Mac Aodha, Rakesh Ranjan
Enhancing 2D Representation Learning with a 3D Prior. CoRR (2024)
Neehar Kondapaneni, Markus Marks, Oisin Mac Aodha, Pietro Perona
Less is More: Discovering Concise Network Explanations. CoRR (2024)
Salvatore Esposito, Qingshan Xu, Kacper Kania, Charlie Hewitt, Octave Mariotti, Lohit Petikam, Julien Valentin, Arno Onken, Oisin Mac Aodha
GeoGen: Geometry-Aware Generative Modeling via Signed Distance Functions. CoRR (2024)
Bingchen Zhao, Nico Lang, Serge J. Belongie, Oisin Mac Aodha
Labeled Data Selection for Category Discovery. CoRR (2024)
Nikolaos Tsagkas, Jack Rome, Subramanian Ramamoorthy, Oisin Mac Aodha, Chris Xiaoxuan Lu
Click to Grasp: Zero-Shot Precise Manipulation via Visual Diffusion Descriptors. CoRR (2024)
Jamie Watson, Filippo Aleotti, Mohamed Sayed, Zawar Qureshi, Oisin Mac Aodha, Gabriel J. Brostow, Michael Firman, Sara Vicente
AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings. CoRR (2024)
Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps. CoRR (2023)
Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha
Active Learning-Based Species Range Estimation. NeurIPS (2023)
Santiago Martinez Balvanera, Oisin Mac Aodha, Matthew J. Weldy, Holly Pringle, Ella Browning, Kate E. Jones
Whombat: An open-source annotation tool for machine learning development in bioacoustics. CoRR (2023)
Elijah Cole, Grant Van Horn, Christian Lange, Alexander Shepard, Patrick Leary, Pietro Perona, Scott Loarie, Oisin Mac Aodha
Spatial Implicit Neural Representations for Global-Scale Species Mapping. CoRR (2023)
Nikolaos Tsagkas, Oisin Mac Aodha, Chris Xiaoxuan Lu
VL-Fields: Towards Language-Grounded Neural Implicit Spatial Representations. CoRR (2023)
Bingchen Zhao, Oisin Mac Aodha
Incremental Generalized Category Discovery. ICCV (2023)
Jamie Watson, Sara Vicente, Oisin Mac Aodha, Clément Godard, Gabriel J. Brostow, Michael Firman
Heightfields for Efficient Scene Reconstruction for AR. WACV (2023)
Yongshuo Zong, Oisin Mac Aodha, Timothy M. Hospedales
Self-Supervised Multimodal Learning: A Survey. CoRR (2023)
Mehmet Aygün, Oisin Mac Aodha
SAOR: Single-View Articulated Object Reconstruction. CoRR (2023)
Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha
Active Learning-Based Species Range Estimation. CoRR (2023)
Bingchen Zhao, Oisin Mac Aodha
Incremental Generalized Category Discovery. CoRR (2023)
Jamie Watson, Mohamed Sayed, Zawar Qureshi, Gabriel J. Brostow, Sara Vicente, Oisin Mac Aodha, Michael Firman
Virtual Occlusions Through Implicit Depth. CoRR (2023)
Elijah Cole, Grant Van Horn, Christian Lange, Alexander Shepard, Patrick Leary, Pietro Perona, Scott Loarie, Oisin Mac Aodha
Spatial Implicit Neural Representations for Global-Scale Species Mapping. ICML (2023)
Jamie Watson, Mohamed Sayed, Zawar Qureshi, Gabriel J. Brostow, Sara Vicente, Oisin Mac Aodha, Michael Firman
Virtual Occlusions Through Implicit Depth. CVPR (2023)
Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
ViewNeRF: Unsupervised Viewpoint Estimation Using Category-Level Neural Radiance Fields. BMVC (2022)
Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation. CoRR (2022)
Kiyoon Kim, Davide Moltisanti, Oisin Mac Aodha, Laura Sevilla-Lara
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition. CoRR (2022)
Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, Serge J. Belongie
When Does Contrastive Visual Representation Learning Work? CVPR (2022)
Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
ViewNeRF: Unsupervised Viewpoint Estimation Using Category-Level Neural Radiance Fields. CoRR (2022)
Kiyoon Kim, Shreyank N. Gowda, Oisin Mac Aodha, Laura Sevilla-Lara
Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition. CoRR (2022)
Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models. CoRR (2022)
Kiyoon Kim, Davide Moltisanti, Oisin Mac Aodha, Laura Sevilla-Lara
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition. BMVC (2022)
Mehmet Aygün, Oisin Mac Aodha
Demystifying Unsupervised Semantic Correspondence Estimation. CoRR (2022)
Neehar Kondapaneni, Pietro Perona, Oisin Mac Aodha
Visual Knowledge Tracing. CoRR (2022)
Xiu-Shen Wei, Yi-Zhe Song, Oisin Mac Aodha, Jianxin Wu, Yuxin Peng, Jinhui Tang, Jian Yang, Serge J. Belongie
Fine-Grained Image Analysis With Deep Learning: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Kiyoon Kim, Shreyank N. Gowda, Oisin Mac Aodha, Laura Sevilla-Lara
Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition. BMVC (2022)
Grant Van Horn, Rui Qian, Kimberly Wilber, Hartwig Adam, Oisin Mac Aodha, Serge J. Belongie
Exploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset. CoRR (2022)
Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha
On Label Granularity and Object Localization. CoRR (2022)
Grant Van Horn, Rui Qian, Kimberly Wilber, Hartwig Adam, Oisin Mac Aodha, Serge J. Belongie
Exploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset. ECCV (8) (2022)
Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge J. Belongie, Andrew G. Howard, Oisin Mac Aodha
On Label Granularity and Object Localization. ECCV (10) (2022)
Mehmet Aygün, Oisin Mac Aodha
Demystifying Unsupervised Semantic Correspondence Estimation. ECCV (30) (2022)
Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models. BMVC (2022)
Neehar Kondapaneni, Pietro Perona, Oisin Mac Aodha
Visual Knowledge Tracing. ECCV (25) (2022)
Jamie Watson, Oisin Mac Aodha, Victor Prisacariu, Gabriel J. Brostow, Michael Firman
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth. CVPR (2021)
Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring. ICCV (2021)
Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, Nebojsa Jojic
Multi-Label Learning from Single Positive Labels. CoRR (2021)
Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, Nebojsa Jojic
Multi-Label Learning From Single Positive Labels. CVPR (2021)
Jamie Watson, Oisin Mac Aodha, Victor Prisacariu, Gabriel J. Brostow, Michael Firman
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth. CoRR (2021)
Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation. ICCV (2021)
Grant Van Horn, Elijah Cole, Sara Beery, Kimberly Wilber, Serge J. Belongie, Oisin Mac Aodha
Benchmarking Representation Learning for Natural World Image Collections. CVPR (2021)
Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring. CoRR (2021)
Xiu-Shen Wei, Yi-Zhe Song, Oisin Mac Aodha, Jianxin Wu, Yuxin Peng, Jinhui Tang, Jian Yang, Serge J. Belongie
Fine-Grained Image Analysis with Deep Learning: A Survey. CoRR (2021)
Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, Serge J. Belongie
When Does Contrastive Visual Representation Learning Work? CoRR (2021)
Grant Van Horn, Elijah Cole, Sara Beery, Kimberly Wilber, Serge J. Belongie, Oisin Mac Aodha
Benchmarking Representation Learning for Natural World Image Collections. CoRR (2021)
Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel J. Brostow, Michael Firman
Learning Stereo from Single Images. CoRR (2020)
Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel J. Brostow, Michael Firman
Learning Stereo from Single Images. ECCV (1) (2020)
Daniel Laumer, Nico Lang, Natalie van Doorn, Oisin Mac Aodha, Pietro Perona, Jan Dirk Wegner
Geocoding of trees from street addresses and street-level images. CoRR (2020)
Oisin Mac Aodha, Elijah Cole, Pietro Perona
Presence-Only Geographical Priors for Fine-Grained Image Classification. CoRR (2019)
Clément Godard, Oisin Mac Aodha, Michael Firman, Gabriel J. Brostow
Digging Into Self-Supervised Monocular Depth Estimation. ICCV (2019)
Sara Beery, Grant Van Horn, Oisin Mac Aodha, Pietro Perona
The iWildCam 2018 Challenge Dataset. CoRR (2019)
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla
Teaching Multiple Concepts to a Forgetful Learner. NeurIPS (2019)
Oisin Mac Aodha, Elijah Cole, Pietro Perona
Presence-Only Geographical Priors for Fine-Grained Image Classification. ICCV (2019)
Matteo Ruggero Ronchi, Oisin Mac Aodha, Robert Eng, Pietro Perona
It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data. BMVC (2018)
Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow
Digging Into Self-Supervised Monocular Depth Estimation. CoRR (2018)
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla
Teaching Multiple Concepts to Forgetful Learners. CoRR (2018)
Matteo Ruggero Ronchi, Oisin Mac Aodha, Robert Eng, Pietro Perona
It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data. CoRR (2018)
Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue
Teaching Categories to Human Learners with Visual Explanations. CoRR (2018)
Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. CoRR (2018)
Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue
Teaching Categories to Human Learners With Visual Explanations. CVPR (2018)
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alexander Shepard, Hartwig Adam, Pietro Perona, Serge J. Belongie
The INaturalist Species Classification and Detection Dataset. CVPR (2018)
Kun Ho Kim, Oisin Mac Aodha, Pietro Perona
Context Embedding Networks. CVPR (2018)
Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. NeurIPS (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 A. Girolami, Gabriel J. Brostow, Kate E. Jones
Bat detective - Deep learning tools for bat acoustic signal detection. PLoS Comput. Biol. 14 (3) (2018)
Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue
Near-Optimal Machine Teaching via Explanatory Teaching Sets. AISTATS (2018)
Kun Ho Kim, Oisin Mac Aodha, Pietro Perona
Context Embedding Networks. CoRR (2017)
Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow
Unsupervised Monocular Depth Estimation with Left-Right Consistency. CVPR (2017)
Grant Van Horn, Oisin Mac Aodha, Yang Song, Alexander Shepard, Hartwig Adam, Pietro Perona, Serge J. Belongie
The iNaturalist Challenge 2017 Dataset. CoRR (2017)
Tom S. F. Haines, Oisin Mac Aodha, Gabriel J. Brostow
My Text in Your Handwriting. ACM Trans. Graph. 35 (3) (2016)
Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow
Unsupervised Monocular Depth Estimation with Left-Right Consistency. CoRR (2016)
Michael Firman, Oisin Mac Aodha, Simon J. Julier, Gabriel J. Brostow
Structured Prediction of Unobserved Voxels from a Single Depth Image. CVPR (2016)
Edward Johns, Oisin Mac Aodha, Gabriel J. Brostow
Becoming the Expert - Interactive Multi-Class Machine Teaching. CoRR (2015)
Oisin Mac Aodha, Neill D. F. Campbell, Jan Kautz, Gabriel J. Brostow
Hierarchical Subquery Evaluation for Active Learning on a Graph. CoRR (2015)
Edward Johns, Oisin Mac Aodha, Gabriel J. Brostow
Becoming the expert - interactive multi-class machine teaching. CVPR (2015)
Oisin Mac Aodha, Vassilios Stathopoulos, Gabriel J. Brostow, Michael Terry, Mark A. Girolami, Kate E. Jones
Putting the Scientist in the Loop - Accelerating Scientific Progress with Interactive Machine Learning. ICPR (2014)
Oisin Mac Aodha, Neill D. F. Campbell, Jan Kautz, Gabriel J. Brostow
Hierarchical Subquery Evaluation for Active Learning on a Graph. CVPR (2014)
Oisin Mac Aodha, Ahmad Humayun, Marc Pollefeys, Gabriel J. Brostow
Learning a Confidence Measure for Optical Flow. IEEE Trans. Pattern Anal. Mach. Intell. 35 (5) (2013)
Oisin Mac Aodha, Gabriel J. Brostow
Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees. ICCV (2013)
Oisin Mac Aodha, Neill D. F. Campbell, Arun Nair, Gabriel J. Brostow
Patch Based Synthesis for Single Depth Image Super-Resolution. ECCV (3) (2012)
Ahmad Humayun, Oisin Mac Aodha, Gabriel J. Brostow
Learning to find occlusion regions. CVPR (2011)
Oisin Mac Aodha, Gabriel J. Brostow, Marc Pollefeys
Segmenting video into classes of algorithm-suitability. CVPR (2010)
John Maher, Fearghal Morgan, Oisin Mac Aodha
Evolving plastic responses in artificial cell models. IEEE Congress on Evolutionary Computation (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Oisin Mac Aodha