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» Learning Low-Level Vision
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ECCV
2010
Springer
13 years 10 months ago
Adapting Visual Category Models to New Domains
Abstract. Domain adaptation is an important emerging topic in computer vision. In this paper, we present one of the first studies of domain shift in the context of object recogniti...
Kate Saenko, Brian Kulis, Mario Fritz, Trevor Darr...
CVPR
2009
IEEE
15 years 4 months ago
D - Clutter: Building object model library from unsupervised segmentation of cluttered scenes
Autonomous systems which learn and utilize a limited visual vocabulary have wide spread applications. Enabling such systems to segment a set of cluttered scenes into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...
CVPR
2011
IEEE
13 years 5 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ACCV
2010
Springer
13 years 4 months ago
Efficient Structured Support Vector Regression
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structu...
Ke Jia, Lei Wang, Nianjun Liu
TROB
2010
159views more  TROB 2010»
13 years 4 months ago
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
Ales Ude, Andrej Gams, Tamim Asfour, Jun Morimoto