We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
We propose a learning method for gait synthesis from a sequence of shapes(frames) with the ability to extrapolate to novel data. It involves the application of PCA, first to redu...
Muayed Sattar Al-Huseiny, Sasan Mahmoodi, Mark Nix...
A framework for photo-realistic view-dependent image synthesis of a shiny object from a sparse set of images and a geometric model is proposed. Each image is aligned with the 3D m...
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A ...
Mike Perkowitz, Matthai Philipose, Kenneth P. Fish...