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Oisin Mac Aodha
Person information
- affiliation: University of Edinburgh, UK
- affiliation (former): Caltech, CA, USA
- affiliation (former): University College London, UK
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2020 – today
- 2024
- [c46]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. CVPR 2024: 5270-5280 - [c45]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. CVPR Workshops 2024: 7479-7488 - [c44]Mehmet Aygün, Prithviraj Dhar, Zhicheng Yan, Oisin Mac Aodha, Rakesh Ranjan:
Enhancing 2D Representation Learning with a 3D Prior. CVPR Workshops 2024: 7750-7760 - [c43]Mehmet Aygün, Oisin Mac Aodha:
SAOR: Single-View Articulated Object Reconstruction. CVPR 2024: 10382-10391 - [c42]Nico Lang, Vésteinn Snæbjarnarson, Elijah Cole, Oisin Mac Aodha, Christian Igel, Serge J. Belongie:
From Coarse to Fine-Grained Open-Set Recognition. CVPR 2024: 17804-17814 - [c41]Octave Mariotti, Oisin Mac Aodha, Hakan Bilen:
Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps. CVPR 2024: 19521-19530 - [c40]Bingchen Zhao, Nico Lang, Serge J. Belongie, Oisin Mac Aodha:
Labeled Data Selection for Category Discovery. ECCV (55) 2024: 201-218 - [i47]Nikolaos Tsagkas, Jack Rome, Subramanian Ramamoorthy, Oisin Mac Aodha, Chris Xiaoxuan Lu:
Click to Grasp: Zero-Shot Precise Manipulation via Visual Diffusion Descriptors. CoRR abs/2403.14526 (2024) - [i46]Neehar Kondapaneni, Markus Marks, Oisin Mac Aodha, Pietro Perona:
Less is More: Discovering Concise Network Explanations. CoRR abs/2405.15243 (2024) - [i45]Mehmet Aygün, Prithviraj Dhar, Zhicheng Yan, Oisin Mac Aodha, Rakesh Ranjan:
Enhancing 2D Representation Learning with a 3D Prior. CoRR abs/2406.02535 (2024) - [i44]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 abs/2406.04254 (2024) - [i43]Bingchen Zhao, Nico Lang, Serge J. Belongie, Oisin Mac Aodha:
Labeled Data Selection for Category Discovery. CoRR abs/2406.04898 (2024) - [i42]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 abs/2406.08960 (2024) - [i41]Omiros Pantazis, Peggy Bevan, Holly Pringle, Guilherme Braga Ferreira, Daniel J. Ingram, Emily Madsen, Liam Thomas, Dol Raj Thanet, Thakur Silwal, Santosh Rayamajhi, Gabriel J. Brostow, Oisin Mac Aodha, Kate E. Jones:
Deep learning-based ecological analysis of camera trap images is impacted by training data quality and size. CoRR abs/2408.14348 (2024) - [i40]Filip Dorm, Christian Lange, Scott Loarie, Oisin Mac Aodha:
Generating Binary Species Range Maps. CoRR abs/2408.15956 (2024) - [i39]Max Hamilton, Christian Lange, Elijah Cole, Alexander Shepard, Samuel Heinrich, Oisin Mac Aodha, Grant Van Horn, Subhransu Maji:
Combining Observational Data and Language for Species Range Estimation. CoRR abs/2410.10931 (2024) - 2023
- [c39]Jamie Watson, Mohamed Sayed, Zawar Qureshi, Gabriel J. Brostow, Sara Vicente, Oisin Mac Aodha, Michael Firman:
Virtual Occlusions Through Implicit Depth. CVPR 2023: 9053-9064 - [c38]Bingchen Zhao, Oisin Mac Aodha:
Incremental Generalized Category Discovery. ICCV 2023: 19080-19090 - [c37]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: 6320-6342 - [c36]Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha:
Active Learning-Based Species Range Estimation. NeurIPS 2023 - [c35]Jamie Watson, Sara Vicente, Oisin Mac Aodha, Clément Godard, Gabriel J. Brostow, Michael Firman:
Heightfields for Efficient Scene Reconstruction for AR. WACV 2023: 5839-5849 - [i38]Mehmet Aygün, Oisin Mac Aodha:
SAOR: Single-View Articulated Object Reconstruction. CoRR abs/2303.13514 (2023) - [i37]Yongshuo Zong, Oisin Mac Aodha, Timothy M. Hospedales:
Self-Supervised Multimodal Learning: A Survey. CoRR abs/2304.01008 (2023) - [i36]Bingchen Zhao, Oisin Mac Aodha:
Incremental Generalized Category Discovery. CoRR abs/2304.14310 (2023) - [i35]Jamie Watson, Mohamed Sayed, Zawar Qureshi, Gabriel J. Brostow, Sara Vicente, Oisin Mac Aodha, Michael Firman:
Virtual Occlusions Through Implicit Depth. CoRR abs/2305.07014 (2023) - [i34]Nikolaos Tsagkas, Oisin Mac Aodha, Chris Xiaoxuan Lu:
VL-Fields: Towards Language-Grounded Neural Implicit Spatial Representations. CoRR abs/2305.12427 (2023) - [i33]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 abs/2306.02564 (2023) - [i32]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 abs/2308.12688 (2023) - [i31]Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha:
Active Learning-Based Species Range Estimation. CoRR abs/2311.02061 (2023) - [i30]Octave Mariotti, Oisin Mac Aodha, Hakan Bilen:
Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps. CoRR abs/2312.13216 (2023) - 2022
- [j4]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): 8927-8948 (2022) - [c34]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: 355 - [c33]Kiyoon Kim, Davide Moltisanti, Oisin Mac Aodha, Laura Sevilla-Lara:
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition. BMVC 2022: 356 - [c32]Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha:
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models. BMVC 2022: 580 - [c31]Octave Mariotti, Oisin Mac Aodha, Hakan Bilen:
ViewNeRF: Unsupervised Viewpoint Estimation Using Category-Level Neural Radiance Fields. BMVC 2022: 740 - [c30]Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, Serge J. Belongie:
When Does Contrastive Visual Representation Learning Work? CVPR 2022: 1-10 - [c29]Mehmet Aygün, Oisin Mac Aodha:
Demystifying Unsupervised Semantic Correspondence Estimation. ECCV (30) 2022: 125-142 - [c28]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: 271-289 - [c27]Neehar Kondapaneni, Pietro Perona, Oisin Mac Aodha:
Visual Knowledge Tracing. ECCV (25) 2022: 415-431 - [c26]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: 604-620 - [i29]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 abs/2201.10394 (2022) - [i28]Mehmet Aygün, Oisin Mac Aodha:
Demystifying Unsupervised Semantic Correspondence Estimation. CoRR abs/2207.05054 (2022) - [i27]Neehar Kondapaneni, Pietro Perona, Oisin Mac Aodha:
Visual Knowledge Tracing. CoRR abs/2207.10157 (2022) - [i26]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 abs/2207.10225 (2022) - [i25]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 abs/2207.10664 (2022) - [i24]Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha:
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models. CoRR abs/2210.03794 (2022) - [i23]Kiyoon Kim, Davide Moltisanti, Oisin Mac Aodha, Laura Sevilla-Lara:
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition. CoRR abs/2210.04933 (2022) - [i22]Octave Mariotti, Oisin Mac Aodha, Hakan Bilen:
ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation. CoRR abs/2212.00435 (2022) - [i21]Octave Mariotti, Oisin Mac Aodha, Hakan Bilen:
ViewNeRF: Unsupervised Viewpoint Estimation Using Category-Level Neural Radiance Fields. CoRR abs/2212.00436 (2022) - 2021
- [c25]Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, Nebojsa Jojic:
Multi-Label Learning From Single Positive Labels. CVPR 2021: 933-942 - [c24]Jamie Watson, Oisin Mac Aodha, Victor Prisacariu, Gabriel J. Brostow, Michael Firman:
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth. CVPR 2021: 1164-1174 - [c23]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: 12884-12893 - [c22]Octave Mariotti, Oisin Mac Aodha, Hakan Bilen:
ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation. ICCV 2021: 10398-10408 - [c21]Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha:
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring. ICCV 2021: 10563-10572 - [i20]Grant Van Horn, Elijah Cole, Sara Beery, Kimberly Wilber, Serge J. Belongie, Oisin Mac Aodha:
Benchmarking Representation Learning for Natural World Image Collections. CoRR abs/2103.16483 (2021) - [i19]Jamie Watson, Oisin Mac Aodha, Victor Prisacariu, Gabriel J. Brostow, Michael Firman:
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth. CoRR abs/2104.14540 (2021) - [i18]Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, Serge J. Belongie:
When Does Contrastive Visual Representation Learning Work? CoRR abs/2105.05837 (2021) - [i17]Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, Nebojsa Jojic:
Multi-Label Learning from Single Positive Labels. CoRR abs/2106.09708 (2021) - [i16]Omiros Pantazis, Gabriel J. Brostow, Kate E. Jones, Oisin Mac Aodha:
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring. CoRR abs/2108.06435 (2021) - [i15]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 abs/2111.06119 (2021) - 2020
- [c20]Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel J. Brostow, Michael Firman:
Learning Stereo from Single Images. ECCV (1) 2020: 722-740 - [i14]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 abs/2002.01708 (2020) - [i13]Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov, Gabriel J. Brostow, Michael Firman:
Learning Stereo from Single Images. CoRR abs/2008.01484 (2020)
2010 – 2019
- 2019
- [c19]Clément Godard, Oisin Mac Aodha, Michael Firman, Gabriel J. Brostow:
Digging Into Self-Supervised Monocular Depth Estimation. ICCV 2019: 3827-3837 - [c18]Oisin Mac Aodha, Elijah Cole, Pietro Perona:
Presence-Only Geographical Priors for Fine-Grained Image Classification. ICCV 2019: 9595-9605 - [c17]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: 4050-4060 - [i12]Sara Beery, Grant Van Horn, Oisin Mac Aodha, Pietro Perona:
The iWildCam 2018 Challenge Dataset. CoRR abs/1904.05986 (2019) - [i11]Oisin Mac Aodha, Elijah Cole, Pietro Perona:
Presence-Only Geographical Priors for Fine-Grained Image Classification. CoRR abs/1906.05272 (2019) - 2018
- [j3]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) - [c16]Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue:
Near-Optimal Machine Teaching via Explanatory Teaching Sets. AISTATS 2018: 1970-1978 - [c15]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: 300 - [c14]Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue:
Teaching Categories to Human Learners With Visual Explanations. CVPR 2018: 3820-3828 - [c13]Kun Ho Kim, Oisin Mac Aodha, Pietro Perona:
Context Embedding Networks. CVPR 2018: 8679-8687 - [c12]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: 8769-8778 - [c11]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: 1483-1493 - [i10]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 abs/1802.05190 (2018) - [i9]Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue:
Teaching Categories to Human Learners with Visual Explanations. CoRR abs/1802.06924 (2018) - [i8]Matteo Ruggero Ronchi, Oisin Mac Aodha, Robert Eng, Pietro Perona:
It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data. CoRR abs/1805.06880 (2018) - [i7]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 abs/1805.08322 (2018) - [i6]Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow:
Digging Into Self-Supervised Monocular Depth Estimation. CoRR abs/1806.01260 (2018) - 2017
- [c10]Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow:
Unsupervised Monocular Depth Estimation with Left-Right Consistency. CVPR 2017: 6602-6611 - [i5]Grant Van Horn, Oisin Mac Aodha, Yang Song, Alexander Shepard, Hartwig Adam, Pietro Perona, Serge J. Belongie:
The iNaturalist Challenge 2017 Dataset. CoRR abs/1707.06642 (2017) - [i4]Kun Ho Kim, Oisin Mac Aodha, Pietro Perona:
Context Embedding Networks. CoRR abs/1710.01691 (2017) - 2016
- [j2]Tom S. F. Haines, Oisin Mac Aodha, Gabriel J. Brostow:
My Text in Your Handwriting. ACM Trans. Graph. 35(3): 26:1-26:18 (2016) - [c9]Michael Firman, Oisin Mac Aodha, Simon J. Julier, Gabriel J. Brostow:
Structured Prediction of Unobserved Voxels from a Single Depth Image. CVPR 2016: 5431-5440 - [i3]Clément Godard, Oisin Mac Aodha, Gabriel J. Brostow:
Unsupervised Monocular Depth Estimation with Left-Right Consistency. CoRR abs/1609.03677 (2016) - 2015
- [c8]Edward Johns, Oisin Mac Aodha, Gabriel J. Brostow:
Becoming the expert - interactive multi-class machine teaching. CVPR 2015: 2616-2624 - [i2]Edward Johns, Oisin Mac Aodha, Gabriel J. Brostow:
Becoming the Expert - Interactive Multi-Class Machine Teaching. CoRR abs/1504.07575 (2015) - [i1]Oisin Mac Aodha, Neill D. F. Campbell, Jan Kautz, Gabriel J. Brostow:
Hierarchical Subquery Evaluation for Active Learning on a Graph. CoRR abs/1504.08219 (2015) - 2014
- [b1]Oisin Mac Aodha:
Supervised algorithm selection for flow and other computer vision problems. University College London, UK, 2014 - [c7]Oisin Mac Aodha, Neill D. F. Campbell, Jan Kautz, Gabriel J. Brostow:
Hierarchical Subquery Evaluation for Active Learning on a Graph. CVPR 2014: 564-571 - [c6]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: 9-17 - 2013
- [j1]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): 1107-1120 (2013) - [c5]Oisin Mac Aodha, Gabriel J. Brostow:
Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees. ICCV 2013: 193-200 - 2012
- [c4]Oisin Mac Aodha, Neill D. F. Campbell, Arun Nair, Gabriel J. Brostow:
Patch Based Synthesis for Single Depth Image Super-Resolution. ECCV (3) 2012: 71-84 - 2011
- [c3]Ahmad Humayun, Oisin Mac Aodha, Gabriel J. Brostow:
Learning to find occlusion regions. CVPR 2011: 2161-2168 - 2010
- [c2]Oisin Mac Aodha, Gabriel J. Brostow, Marc Pollefeys:
Segmenting video into classes of algorithm-suitability. CVPR 2010: 1054-1061
2000 – 2009
- 2009
- [c1]John Maher, Fearghal Morgan, Oisin Mac Aodha:
Evolving plastic responses in artificial cell models. IEEE Congress on Evolutionary Computation 2009: 3018-3023
Coauthor Index
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