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» ClassMap: Efficient Multiclass Recognition via Embeddings
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ICCV
2007
IEEE
9 years 2 months ago
ClassMap: Efficient Multiclass Recognition via Embeddings
In many computer vision applications, such as face recognition and hand pose estimation, we need systems that can recognize a very large number of classes. Large margin classifica...
Vassilis Athitsos, Alexandra Stefan, Quan Yuan, St...
ICCV
2009
IEEE
8 years 8 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
ICIP
2005
IEEE
10 years 6 hour ago
Expression-invariant face recognition via spherical embedding
Recently, it was proven empirically that facial expressions can be modelled as isometries, that is, geodesic distances on the facial surface were shown to be significantly less se...
Alexander M. Bronstein, Michael M. Bronstein, Ron ...
CVPR
2003
IEEE
10 years 11 days ago
Many-to-Many Graph Matching via Metric Embedding
Graph matching is an important component in many object recognition algorithms. Although most graph matching algorithms seek a one-to-one correspondence between nodes, it is often...
Yakov Keselman, Ali Shokoufandeh, M. Fatih Demirci...
ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
10 years 3 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...
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