42 citations · 156 across the 16 of their papers we have counts for
4 papers · 1 filter
SAGE: Saliency-Guided Mixup with Optimal Rearrangements
Avery Ma, Nikita Dvornik, Ran Zhang +3
Data augmentation is a key element for training accurate models by reducing overfitting and improving generalization. For image classification, the most popular data augmentation t…
Uncertainty-based Cross-Modal Retrieval with Probabilistic Representations
Leila Pishdad, Ran Zhang, Konstantinos G. Derpanis +2
Probabilistic embeddings have proven useful for capturing polysemous word meanings, as well as ambiguity in image matching. In this paper, we study the advantages of probabilistic…
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning
Karl Pertsch, Oleh Rybkin, Jingyun Yang +5
Temporal observations such as videos contain essential information about the dynamics of the underlying scene, but they are often interleaved with inessential, predictable details.…
Learning what you can do before doing anything
Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis +2
Intelligent agents can learn to represent the action spaces of other agents simply by observing them act. Such representations help agents quickly learn to predict the effects of t…