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ECCV
2010
Springer
14 years 19 days ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ECCV
2006
Springer
15 years 2 months ago
Feature Harvesting for Tracking-by-Detection
We propose a fast approach to 3?D object detection and pose estimation that owes its robustness to a training phase during which the target object slowly moves with respect to the ...
Mustafa Özuysal, Vincent Lepetit, Franç...