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Oisin Mac Aodha
Oisin Mac Aodha
Reader (Associate Professor), University of Edinburgh
Dirección de correo verificada de ed.ac.uk - Página principal
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Unsupervised monocular depth estimation with left-right consistency
C Godard, O Mac Aodha, GJ Brostow
Proceedings of the IEEE conference on computer vision and pattern …, 2017
35352017
Digging into self-supervised monocular depth estimation
C Godard, O Mac Aodha, M Firman, GJ Brostow
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
25192019
The inaturalist species classification and detection dataset
G Van Horn, O Mac Aodha, Y Song, Y Cui, C Sun, A Shepard, H Adam, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
1763*2018
The temporal opportunist: Self-supervised multi-frame monocular depth
J Watson, O Mac Aodha, V Prisacariu, G Brostow, M Firman
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
2722021
Fine-grained image analysis with deep learning: A survey
XS Wei, YZ Song, O Mac Aodha, J Wu, Y Peng, J Tang, J Yang, ...
IEEE transactions on pattern analysis and machine intelligence 44 (12), 8927 …, 2021
2602021
Patch based synthesis for single depth image super-resolution
O Mac Aodha, NDF Campbell, A Nair, GJ Brostow
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
2552012
Bat detective—Deep learning tools for bat acoustic signal detection
O Mac Aodha, R Gibb, KE Barlow, E Browning, M Firman, R Freeman, ...
PLoS computational biology 14 (3), e1005995, 2018
2422018
Hierarchical subquery evaluation for active learning on a graph
O Mac Aodha, NDF Campbell, J Kautz, GJ Brostow
Proceedings of the IEEE conference on computer vision and pattern …, 2014
2422014
Structured prediction of unobserved voxels from a single depth image
M Firman, O Mac Aodha, S Julier, GJ Brostow
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
2002016
Presence-only geographical priors for fine-grained image classification
O Mac Aodha, E Cole, P Perona
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
1582019
Benchmarking representation learning for natural world image collections
G Van Horn, E Cole, S Beery, K Wilber, S Belongie, O Mac Aodha
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
1532021
When does contrastive visual representation learning work?
E Cole, X Yang, K Wilber, O Mac Aodha, S Belongie
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
138*2022
Learning a confidence measure for optical flow
O Mac Aodha, A Humayun, M Pollefeys, GJ Brostow
IEEE transactions on pattern analysis and machine intelligence 35 (5), 1107-1120, 2012
1282012
Multi-label learning from single positive labels
E Cole, O Mac Aodha, T Lorieul, P Perona, D Morris, N Jojic
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
112*2021
Becoming the expert-interactive multi-class machine teaching
E Johns, O Mac Aodha, GJ Brostow
Proceedings of the IEEE conference on computer vision and pattern …, 2015
892015
Teaching categories to human learners with visual explanations
O Mac Aodha, S Su, Y Chen, P Perona, Y Yue
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
832018
Learning to find occlusion regions
A Humayun, O Mac Aodha, GJ Brostow
CVPR 2011, 2161-2168, 2011
782011
My Text in Your Handwriting
TSF Haines, O Mac Aodha, GJ Brostow
ACM Transactions on Graphics (TOG) 35 (3), 26, 2016
68*2016
Segmenting video into classes of algorithm-suitability
O Mac Aodha, GJ Brostow, M Pollefeys
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010
682010
Predicting depth from image data using a statistical model
C Godard, O MacAodha, G Brostow
US Patent 11,100,401, 2021
672021
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Artículos 1–20