Sciweavers

CVPR
2010
IEEE
14 years 8 months ago
Exploiting Hierarchical Context on a Large Database of Object Categories
There has been a growing interest in exploiting contextual information in addition to local features to detect and localize multiple object categories in an image. Context models ...
Myung Jin Choi, Joseph Lim, Antonio Torralba, Alan...
ICIP
2009
IEEE
15 years 27 days ago
Learning Contextual Rules For Priming Object Categories In Images
In this paper we introduce and exploit the concept of contextual rules in the field of object detection. These rules are defined as associations between different object likelihoo...
ICPR
2004
IEEE
15 years 29 days ago
Object Recognition Using Segmentation for Feature Detection
: A new method is presented to learn object categories from unlabeled and unsegmented images for generic object recognition. We assume that each object can be characterized by a se...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
ICPR
2008
IEEE
15 years 1 months ago
Layered object categorization
In this paper, we propose a novel framework of object categorization, namely layered object categorization, which takes advantage of hierarchical category information and performs...
Hong Cheng, Jie Yang, Lei Yang, Nanning Zheng
ECCV
2004
Springer
15 years 1 months ago
A Visual Category Filter for Google Images
We extend the constellation model to include heterogeneous parts which may represent either the appearance or the geometry of a region of the object. The parts and their spatial co...
Robert Fergus, Pietro Perona, Andrew Zisserman
ECCV
2008
Springer
15 years 1 months ago
Saliency Based Opportunistic Search for Object Part Extraction and Labeling
We study the task of object part extraction and labeling, which seeks to understand objects beyond simply identifiying their bounding boxes. We start from bottom-up segmentation of...
Yang Wu, Qihui Zhu, Jianbo Shi, Nanning Zheng
ECCV
2008
Springer
15 years 1 months ago
Towards Scalable Dataset Construction: An Active Learning Approach
As computer vision research considers more object categories and greater variation within object categories, it is clear that larger and more exhaustive datasets are necessary. How...
Brendan Collins, Jia Deng, Kai Li, Fei-Fei Li 0002
ICCV
2003
IEEE
15 years 1 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
ICCV
2005
IEEE
15 years 1 months ago
An Expectation Maximization Approach to the Synergy between Image Segmentation and Object Categorization
In this work we deal with the problem of modelling and exploiting the interaction between the processes of image segmentation and object categorization. We propose a novel framewo...
Iasonas Kokkinos, Petros Maragos
ICCV
2007
IEEE
15 years 1 months ago
Image Classification using Random Forests and Ferns
We explore the problem of classifying images by the object categories they contain in the case of a large number of object categories. To this end we combine three ingredients: (i...
Andrew Zisserman, Anna Bosch, Xavier Muñoz