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NIPS
2004
13 years 11 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
ICCV
2009
IEEE
15 years 3 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
CVPR
2003
IEEE
15 years 12 days ago
Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field
This paper presents a generative model based approach to man-made structure detection in 2D natural images. The proposed approach uses a causal multiscale random field suggested i...
Sanjiv Kumar, Martial Hebert
ECCV
2006
Springer
15 years 8 days ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
ICPR
2002
IEEE
14 years 11 months ago
A Neural Architecture for Fast and Robust Face Detection
In this paper, we present a connectionist approach for detecting and precisely localizing semi-frontal human faces in complex images, making no assumption about the content or the...
Christophe Garcia, Manolis Delakis