226 citations · 289 across the 12 of their papers we have counts for
4 papers · 1 filter
A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts
Yizhe Zhu, Mohamed Elhoseiny, Bingchen Liu +2
Most existing zero-shot learning methods consider the problem as a visual semantic embedding one. Given the demonstrated capability of Generative Adversarial Networks(GANs) to gene…
Link the head to the "beak": Zero Shot Learning from Noisy Text Description at Part Precision
Mohamed Elhoseiny, Yizhe Zhu, Han Zhang +1
In this paper, we study learning visual classifiers from unstructured text descriptions at part precision with no training images. We propose a learning framework that is able to c…
CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms
Ahmed Elgammal, Bingchen Liu, Mohamed Elhoseiny +1
We propose a new system for generating art. The system generates art by looking at art and learning about style; and becomes creative by increasing the arousal potential of the gen…
Overlapping Cover Local Regression Machines
Mohamed Elhoseiny, Ahmed Elgammal
We present the Overlapping Domain Cover (ODC) notion for kernel machines, as a set of overlapping subsets of the data that covers the entire training set and optimized to be spatia…