Aodha, O.M.[Oisin Mac]
* 2010: Segmenting video into classes of algorithm-suitability
* 2011: Learning to find occlusion regions
* 2012: Patch Based Synthesis for Single Depth Image Super-Resolution
* 2013: Learning a Confidence Measure for Optical Flow
* 2013: Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees
* 2014: Hierarchical Subquery Evaluation for Active Learning on a Graph
* 2014: Putting the Scientist in the Loop: Accelerating Scientific Progress with Interactive Machine Learning
* 2015: Becoming the expert: Interactive multi-class machine teaching
* 2016: Structured Prediction of Unobserved Voxels from a Single Depth Image
* 2017: Unsupervised Monocular Depth Estimation with Left-Right Consistency
* 2018: Context Embedding Networks
* 2018: iNaturalist Species Classification and Detection Dataset, The
* 2018: Teaching Categories to Human Learners with Visual Explanations
* 2019: Digging Into Self-Supervised Monocular Depth Estimation
* 2019: Presence-Only Geographical Priors for Fine-Grained Image Classification
* 2020: Learning Stereo from Single Images
* 2021: Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring
* 2021: Multi-Label Learning from Single Positive Labels
* 2021: Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth, The
* 2021: ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation
* 2022: Demystifying Unsupervised Semantic Correspondence Estimation
* 2022: Exploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset
* 2022: Fine-Grained Image Analysis with Deep Learning: A Survey
* 2022: On Label Granularity and Object Localization
* 2022: Visual Knowledge Tracing
* 2022: When Does Contrastive Visual Representation Learning Work?
* 2023: Heightfields for Efficient Scene Reconstruction for AR
* 2023: Incremental Generalized Category Discovery
* 2023: Virtual Occlusions Through Implicit Depth
Includes: Aodha, O.M.[Oisin Mac] Aodha, O.M.
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