Topic models have recently emerged as powerful tools for modeling topical trends in documents. Often the resulting topics are broad and generic, associating large groups of people...
Vidit Jain, Erik G. Learned-Miller, Andrew McCallu...
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
A novel method unifying viewer and model centered approaches for representing structurally complex 3-D objects like human faces is presented. The uni ed 3D frequency-domain repres...
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...