In this paper, we propose the use of the Maximum Entropy approach for the task of automatic image annotation. Given labeled training data, Maximum Entropy is a statistical techniqu...
We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
Crowd-sourcing tools such as Mechanical Turk are popular for annotation of large scale image data sets. Typically, these annotations consist of bounding boxes or coarse outlines o...
In this paper, we investigate a search-based face annotation framework by mining weakly labeled facial images that are freely available on the internet. A key component of such a ...