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DAGM
2006
Springer
13 years 11 months ago
Cross-Articulation Learning for Robust Detection of Pedestrians
Recognizing categories of articulated objects in real-world scenarios is a challenging problem for today's vision algorithms. Due to the large appearance changes and intra-cla...
Edgar Seemann, Bernt Schiele
CVPR
2003
IEEE
14 years 9 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2007
IEEE
14 years 9 months ago
An Exemplar Model for Learning Object Classes
We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. T...
Ondrej Chum, Andrew Zisserman
CVPR
2007
IEEE
14 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
CVPR
2010
IEEE
14 years 3 months ago
Layered Object Detection for Multi-Class Segmentation
We formulate a layered model for object detection and multi-class segmentation. Our system uses the output of a bank of object detectors in order to define shape priors for suppo...
Yi Yang, Sam Hallman, Deva Ramanan, Charless Fowlk...