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CVPR
2008
IEEE
14 years 5 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
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 ...
PAMI
2012
11 years 6 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
ICCV
2005
IEEE
13 years 9 months ago
LOCUS: Learning Object Classes with Unsupervised Segmentation
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
John M. Winn, Nebojsa Jojic
ICIP
2005
IEEE
14 years 5 months ago
Using appearance and context for outdoor scene object classification
We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down contr...
Anna Bosch, Joan Martí, Xavier Muñoz
ICPR
2006
IEEE
14 years 4 months ago
Object and Scene Classification: what does a Supervised Approach Provide us?
Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurre...
Anna Bosch, Arnau Oliver, Robert Marti, Xavier Mu&...