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» Object correspondence as a machine learning problem
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ICML
2005
IEEE
14 years 8 months ago
Object correspondence as a machine learning problem
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
Bernhard Schölkopf, Florian Steinke, Volker B...
ICML
2010
IEEE
13 years 8 months ago
Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences
This paper studies the problem of learning from ambiguous supervision, focusing on the task of learning semantic correspondences. A learning problem is said to be ambiguously supe...
Antoine Bordes, Nicolas Usunier, Jason Weston
IPMI
2003
Springer
14 years 8 months ago
Learning Object Correspondences with the Observed Transport Shape Measure
Abstract. We propose a learning method which introduces explicit knowledge to the object correspondence problem. Our approach uses an a priori learning set to compute a dense corre...
Alain Pitiot, Hervé Delingette, Arthur W. T...
ICML
2006
IEEE
14 years 8 months ago
Ranking on graph data
In ranking, one is given examples of order relationships among objects, and the goal is to learn from these examples a real-valued ranking function that induces a ranking or order...
Shivani Agarwal
MVA
2010
229views Computer Vision» more  MVA 2010»
13 years 2 months ago
Robust 3D object registration without explicit correspondence using geometric integration
3D vision guided manipulation of components is a key problem of industrial machine vision. In this paper, we focus on the localization and pose estimation of known industrial objec...
Dirk Breitenreicher, Christoph Schnörr