We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
The latest multi-biometric grand challenge (MBGC 2008) sets up a new experiment in which near infrared (NIR) face videos containing partial faces are used as a probe set and the vi...
Interpreting the relevance of a user-contributed tag with respect to the visual content of an image is an emerging problem in social image retrieval. In the literature this proble...
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...