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CVPR
2009
IEEE
16 years 8 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
CVPR
2009
IEEE
3784views Computer Vision» more  CVPR 2009»
16 years 7 months ago
What is the Spatial Extent of an Object?
This paper discusses the question: Can we improve the recognition of objects by using their spatial context? We start from Bag-of-Words models and use the Pascal 2007 dataset. We u...
Arnold W. M. Smeulders, Jasper R. R. Uijlings, Rem...
120
Voted
ICCV
2009
IEEE
1331views Computer Vision» more  ICCV 2009»
16 years 5 months ago
I know what you did last summer: object-level auto-annotation of holiday snaps
The state-of-the art in visual object retrieval from large databases allows to search millions of images on the object level. Recently, complementary works have proposed systems ...
Stephan Gammeter, Lukas Bossard, Till Quack, Luc V...
80
Voted
ICCV
2009
IEEE
16 years 5 months ago
What is the Best Multi-Stage Architecture for Object Recognition?
In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer...
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio R...
127
Voted
CVPR
2007
IEEE
16 years 2 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman