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» Learning to localize detected objects
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CVPR
2004
IEEE
14 years 6 months ago
Learning Object Detection from a Small Number of Examples: The Importance of Good Features
Face detection systems have recently achieved high detection rates[11, 8, 5] and real-time performance[11]. However, these methods usually rely on a huge training database (around...
Kobi Levi, Yair Weiss
ECCV
2010
Springer
13 years 8 months ago
Recursive Coarse-to-Fine Localization for fast Object Detection
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors a...
Marco Pedersoli, Jordi Gonzàlez, Andrew D. Bagdan...
ICCV
2007
IEEE
14 years 6 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
DAGM
2008
Springer
13 years 6 months ago
A Multiple Kernel Learning Approach to Joint Multi-class Object Detection
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
Christoph H. Lampert, Matthew B. Blaschko
WAPCV
2007
Springer
13 years 11 months ago
Context Driven Focus of Attention for Object Detection
Abstract. Context plays an important role in general scene perception. In particular, it can provide cues about an object’s location within an image. In computer vision, object d...
Roland Perko, Ales Leonardis