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CVPR
2009
IEEE
15 years 14 days ago
Learning from Ambiguously Labeled Images
In many image and video collections, we have access only to partially labeled data. For example, personal photo collections often contain several faces per image and a caption t...
Benjamin Sapp, Benjamin Taskar, Chris Jordan, Timo...
CVPR
2009
IEEE
15 years 14 days ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori
CVPR
2009
IEEE
15 years 14 days ago
Rank Priors for Continuous Non-Linear Dimensionality Reduction
Non-linear dimensionality reductionmethods are powerful techniques to deal with high-dimensional datasets. However, they often are susceptible to local minima and perform poorly ...
Andreas Geiger (Karlsruhe Institute of Technology)...
CVPR
2009
IEEE
15 years 14 days ago
Global Optimization for Alignment of Generalized Shapes
In this paper, we introduce a novel algorithm to solve global shape registration problems. We use gray-scale “images” to represent source shapes, and propose a novel twocompo...
Hongsheng Li (Lehigh University), Tian Shen (Lehig...
CVPR
2009
IEEE
15 years 14 days ago
Unsupervised Maximum Margin Feature Selection with Manifold Regularization
Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature s...
Bin Zhao, James Tin-Yau Kwok, Fei Wang, Changshui ...
CVPR
2009
IEEE
15 years 14 days ago
Unsupervised Learning for Graph Matching
Graph matching is an important problem in computer vision. It is used in 2D and 3D object matching and recognition. Despite its importance, there is little literature on learnin...
Marius Leordeanu, Martial Hebert
CVPR
2009
IEEE
15 years 14 days ago
Learning a Distance Metric from Multi-instance Multi-label Data
Multi-instance multi-label learning (MIML) refers to the learning problems where each example is represented by a bag/collection of instances and is labeled by multiple labels. ...
Rong Jin (Michigan State University), Shijun Wang...
CVPR
2009
IEEE
15 years 14 days ago
Learning Shape Prior Models for Object Matching
The aim of this work is to learn a shape prior model for an object class and to improve shape matching with the learned shape prior. Given images of example instances, we can le...
Cordelia Schmid, Frédéric Jurie, Tin...
CVPR
2009
IEEE
15 years 14 days ago
Global Connectivity Potentials for Random Field Models
Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions a...
Sebastian Nowozin, Christoph H. Lampert
CVPR
2009
IEEE
15 years 14 days ago
On the Set of Images Modulo Viewpoint and Contrast Changes
We consider regions of images that exhibit smooth statistics, and pose the question of characterizing the “essence” of these regions that matters for visual recognition. Ideal...
Ganesh Sundaramoorthi (UCLA), Peter Petersen (UCLA...