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CVPR
2009
IEEE
17 years 1 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
CVPR
2009
IEEE
1528views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Structured Output-Associative Regression
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
Liefeng Bo and Cristian Sminchisescu
CVPR
2007
IEEE
16 years 8 months ago
Multi-scale Structural Saliency for Signature Detection
Detecting and segmenting free-form objects from cluttered backgrounds is a challenging problem in computer vision. Signature detection in document images is one classic example an...
Guangyu Zhu, Yefeng Zheng, David S. Doermann, Stef...
ICCV
1999
IEEE
16 years 8 months ago
Neurocalibration: A Neural Network That Can Tell Camera Calibration Parameters
Camera calibration is a primary crucial step in many computer vision tasks. In this paper we present a new neural approach for camera calibration. Unlike some existing neural appr...
Moumen T. Ahmed, Elsayed E. Hemayed, Aly A. Farag
ECCV
2008
Springer
16 years 8 months ago
Efficient Edge-Based Methods for Estimating Manhattan Frames in Urban Imagery
We address the problem of efficiently estimating the rotation of a camera relative to the canonical 3D Cartesian frame of an urban scene, under the so-called "Manhattan World&...
Patrick Denis, James H. Elder, Francisco J. Estrad...