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» The Dark Side of Object Learning: Learning Objects
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ICCV
2005
IEEE
14 years 1 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla
EVOW
2010
Springer
13 years 11 months ago
Towards Automated Learning of Object Detectors
Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video seque...
Marc Ebner
ICCV
2003
IEEE
14 years 9 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
ICCV
2005
IEEE
14 years 1 months ago
Object Detection in Aerial Imagery Based on Enhanced Semi-Supervised Learning
Object detection in aerial imagery has been well studied in computer vision for years. However, given the complexity of large variations of the appearance of the object and the ba...
Jian Yao, Zhongfei (Mark) Zhang
AAAI
1996
13 years 9 months ago
A Hybrid Learning Approach for Better Recognition of Visual Objects
Real world images often contain similar objects but with different rotations, noise, or other visual alterations. Vision systems should be able to recognize objects regardless of ...
Ibrahim F. Imam, Srinivas Gutta