27 citations · 98 across the 38 of their papers we have counts for
5 papers · 1 filter
Digging Into Self-Supervised Monocular Depth Estimation
Clément Godard, Oisin Mac Aodha, Michael Firman +1
Per-pixel ground-truth depth data is challenging to acquire at scale. To overcome this limitation, self-supervised learning has emerged as a promising alternative for training mode…
Teaching Multiple Concepts to a Forgetful Learner
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha +5
How can we help a forgetful learner learn multiple concepts within a limited time frame? While there have been extensive studies in designing optimal schedules for teaching a singl…
It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data
Matteo Ruggero Ronchi, Oisin Mac Aodha, Robert Eng +1
We address the problem of 3D human pose estimation from 2D input images using only weakly supervised training data. Despite showing considerable success for 2D pose estimation, the…
Teaching Categories to Human Learners with Visual Explanations
Oisin Mac Aodha, Shihan Su, Yuxin Chen +2
We study the problem of computer-assisted teaching with explanations. Conventional approaches for machine teaching typically only provide feedback at the instance level e.g., the c…
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners
Yuxin Chen, Adish Singla, Oisin Mac Aodha +2
In real-world applications of education, an effective teacher adaptively chooses the next example to teach based on the learner's current state. However, most existing work in algo…