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CVPR
2009
IEEE
16 years 4 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Feature Correspondence and Deformable Object Matching via Agglomerative Correspondence Clustering
We present an efficient method for feature correspondence and object-based image matching, which exploits both photometric similarity and pairwise geometric consistency from local ...
Minsu Cho (Seoul National University), Jungmin Lee...
CVPR
2005
IEEE
15 years 11 months ago
Multi-Output Regularized Projection
Dimensionality reduction via feature projection has been widely used in pattern recognition and machine learning. It is often beneficial to derive the projections not only based o...
Kai Yu, Shipeng Yu, Volker Tresp
CVPR
2007
IEEE
15 years 11 months ago
Mapping Natural Image Patches by Explicit and Implicit Manifolds
Image patches are fundamental elements for object modeling and recognition. However, there has not been a panoramic study of the structures of the whole ensemble of natural image ...
Kent Shi, Song Chun Zhu
CVPR
2007
IEEE
15 years 11 months ago
Leveraging temporal, contextual and ordering constraints for recognizing complex activities in video
We present a scalable approach to recognizing and describing complex activities in video sequences. We are interested in long-term, sequential activities that may have several par...
Benjamin Laxton, Jongwoo Lim, David J. Kriegman