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ICCV
2009
IEEE
10 years 8 months ago
Detecting Objects in Large Image Collections and Videos by Efficient Subimage Retrieval
We study the task of detecting the occurrence of objects in large image collections or in videos, a problem that combines aspects of content based image retrieval and object locali...
Christoph H. Lampert
ICCV
2009
IEEE
10 years 8 months ago
Quantifying Contextual Information for Object Detection
Context is critical for minimising ambiguity in object de- tection. In this work, a novel context modelling framework is proposed without the need of any prior scene segmen- tat...
Wei-Shi Zheng, Shaogang Gong and Tao Xiang
ICCV
2009
IEEE
10 years 8 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
ICCV
2009
IEEE
10 years 8 months ago
Max-Margin Additive Classifiers for Detection
We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piece-wise linear classifiers, which ...
Subhransu Maji, Alexander C. Berg

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SenjianPostdoctoral
Senjian
CVPR
2009
IEEE
10 years 10 months ago
Discriminative Structure Learning of Hierarchical Representations for Object Detection
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
CVPR
2009
IEEE
10 years 10 months ago
Learning color and locality cues for moving object detection and segmentation
This paper presents an algorithm for automatically detecting and segmenting a moving object from a monocular video. Detecting and segmenting a moving object from a video with limit...
Feng Liu (University of Wisconsin-Madison), Michae...
CVPR
2009
IEEE
10 years 10 months ago
Constrained Marginal Space Learning for Efficient 3D Anatomical Structure Detection in Medical Images
Recently, we proposed marginal space learning (MSL) as a generic approach for automatic detection of 3D anatom- ical structures in many medical imaging modalities. To accurately...
Yefeng Zheng, Bogdan Georgescu, Haibin Ling, Shaoh...
CVPR
2009
IEEE
10 years 11 months ago
Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer
We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly be...
Christoph H. Lampert, Hannes Nickisch, Stefan Harm...
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