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DAGM
2011
Springer
12 years 7 months ago
Agnostic Domain Adaptation
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Alexander Vezhnevets, Joachim M. Buhmann
ICPR
2000
IEEE
13 years 12 months ago
Moving Shadow and Object Detection in Traffic Scenes
We present an algorithm for segmentation of traffic scenes that distinguishes moving objects from cast shadows. Three image features at each pixel site are considered: brightness,...
Ivana Mikic, Pamela C. Cosman, Greg T. Kogut, Moha...
CLOR
2006
13 years 11 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
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...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2004
IEEE
14 years 9 months ago
Capturing Image Structure with Probabilistic Index Maps
One of the major problems in modeling images for vision tasks is that images with very similar structure may locally have completely different appearance, e.g., images taken under...
Nebojsa Jojic, Yaron Caspi
ICCV
2005
IEEE
14 years 1 months ago
Resolving Hand over Face Occlusion
Abstract. This paper presents a method to segment the hand over complex backgrounds, such as the face. The similar colors and texture of the hand and face make the problem particul...
Paul Smith, Niels da Vitoria Lobo, Mubarak Shah