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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
CVPR
2008
IEEE
15 years 12 months ago
Pair-activity classification by bi-trajectories analysis
In this paper, we address the pair-activity classification problem, which explores the relationship between two active objects based on their motion information. Our contributions...
Yue Zhou, Shuicheng Yan, Thomas S. Huang
CVPR
2008
IEEE
15 years 12 months ago
Segmentation by transduction
This paper addresses the problem of segmenting an image into regions consistent with user-supplied seeds (e.g., a sparse set of broad brush strokes). We view this task as a statis...
Florent Ségonne, Jean Ponce, Jean-Yves Audi...
ICCV
2007
IEEE
15 years 11 months ago
Recovering Occlusion Boundaries from a Single Image
Occlusion reasoning, necessary for tasks such as navigation and object search, is an important aspect of everyday life and a fundamental problem in computer vision. We believe tha...
Derek Hoiem, Andrew N. Stein, Alexei A. Efros, Mar...
ICCV
2003
IEEE
15 years 11 months ago
Discriminative Random Fields: A Discriminative Framework for Contextual Interaction in Classification
In this work we present Discriminative Random Fields (DRFs), a discriminative framework for the classification of image regions by incorporating neighborhood interactions in the l...
Sanjiv Kumar, Martial Hebert