50 citations · 76 across the 10 of their papers we have counts for
8 papers · 1 filter
High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks
Amir Rosenfeld, Richard Zemel, John K. Tsotsos
Predicting human perceptual similarity is a challenging subject of ongoing research. The visual process underlying this aspect of human vision is thought to employ multiple differe…
Totally Looks Like - How Humans Compare, Compared to Machines
Amir Rosenfeld, Markus D. Solbach, John K. Tsotsos
Perceptual judgment of image similarity by humans relies on rich internal representations ranging from low-level features to high-level concepts, scene properties and even cultural…
Priming Neural Networks
Amir Rosenfeld, Mahdi Biparva, John K. Tsotsos
Visual priming is known to affect the human visual system to allow detection of scene elements, even those that may have been near unnoticeable before, such as the presence of camo…
Incremental Learning Through Deep Adaptation
Amir Rosenfeld, John K. Tsotsos
Given an existing trained neural network, it is often desirable to learn new capabilities without hindering performance of those already learned. Existing approaches either learn s…
Action Classification via Concepts and Attributes
Amir Rosenfeld, Shimon Ullman
Classes in natural images tend to follow long tail distributions. This is problematic when there are insufficient training examples for rare classes. This effect is emphasized in c…
Visual Concept Recognition and Localization via Iterative Introspection
Amir Rosenfeld, Shimon Ullman
Convolutional neural networks have been shown to develop internal representations, which correspond closely to semantically meaningful objects and parts, although trained solely on…
Face-space Action Recognition by Face-Object Interactions
Amir Rosenfeld, Shimon Ullman
Action recognition in still images has seen major improvement in recent years due to advances in human pose estimation, object recognition and stronger feature representations. How…
Hand-Object Interaction and Precise Localization in Transitive Action Recognition
Amir Rosenfeld, Shimon Ullman
Action recognition in still images has seen major improvement in recent years due to advances in human pose estimation, object recognition and stronger feature representations prod…