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» Object correspondence as a machine learning problem
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ICML
2005
IEEE
14 years 5 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 5 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 5 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 5 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»
12 years 11 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