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» Learning object class detectors from weakly annotated video
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ECCV
2006
Springer
14 years 6 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
ICPR
2010
IEEE
13 years 9 months ago
Active Boosting for Interactive Object Retrieval
This paper presents a new algorithm based on boosting for interactive object retrieval in images. Recent works propose ”online boosting” algorithms where weak classifier sets...
Alexis Lechervy, Philippe Henri Gosselin, Frederic...
TRECVID
2008
13 years 6 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
BMVC
2010
13 years 2 months ago
On-line Adaption of Class-specific Codebooks for Instance Tracking
Off-line trained class-specific object detectors are designed to detect any instance of the class in a given image or video sequence. In the context of object tracking, however, o...
Juergen Gall, Nima Razavi, Luc J. Van Gool
CVPR
2008
IEEE
13 years 6 months ago
Optimizing discrimination-efficiency tradeoff in integrating heterogeneous local features for object detection
A large variety of image features has been invented for detection of objects of a known class. We propose a framework to optimize the discrimination-efficiency tradeoff in integra...
Bo Wu, Ram Nevatia