26 search results - page 1 / 6 » Unsupervised learning of translation invariant occlusive com... |
106
Voted
CVPR
2012
IEEE
13 years 18 days ago
2012
IEEE
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
98
Voted
CVPR
2003
IEEE
16 years 6 days ago
2003
IEEE
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
CVPR
2005
IEEE
16 years 6 days ago
2005
IEEE
Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
87
Voted
CVPR
2010
IEEE
15 years 6 months ago
2010
IEEE
Classification of images in many category datasets has
rapidly improved in recent years. However, systems that
perform well on particular datasets typically have one or
more lim...
93
Voted
CVPR
2008
IEEE
16 years 6 days ago
2008
IEEE
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...