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CVPR
2009
IEEE
17 years 2 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
CVPR
2009
IEEE
1084views Computer Vision» more  CVPR 2009»
17 years 2 months ago
Describing Objects by their Attributes
We propose to shift the goal of recognition from naming to describing. Doing so allows us not only to name familiar objects, but also: to report unusual aspects of a familiar ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...
CVPR
2009
IEEE
17 years 2 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
2007
IEEE
16 years 9 months ago
Incremental Linear Discriminant Analysis Using Sufficient Spanning Set Approximations
This paper presents a new incremental learning solution for Linear Discriminant Analysis (LDA). We apply the concept of the sufficient spanning set approximation in each update st...
Björn Stenger, Josef Kittler, Roberto Cipolla...
CVPR
2008
IEEE
16 years 9 months ago
Hierarchical, learning-based automatic liver segmentation
In this paper we present a hierarchical, learning-based approach for automatic and accurate liver segmentation from 3D CT volumes. We target CT volumes that come from largely dive...
Haibin Ling, Shaohua Kevin Zhou, Yefeng Zheng, Bog...