Moving toward zero-shot learning via analogy and imagination
Abstract
While computer vision has progressed rapidly in recent years, humans are still far superior in tasks where there are few (or even zero) examples of the target object in a visual search task. This project will address applications in visual object recognition where a human user must communicate to an autonomous system a desired object. How can the user communicate to the agent most effectively about which object to search for in the environment? How should the user communicate to the agent about a desired object that is not currently known to the agent? The proposed project will explore two algorithmic frameworks that leverage the low-dimensional structure of natural images for addressing these questions: learning through visual imagination and learning by analogy.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 22, 2016
- Source ID
- N000141512619
Entities
People
- Christopher J. Rozell
Organizations
- Georgia Tech Research Corporation
- Office of Naval Research
- United States Navy