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CVPR
2009
IEEE
15 years 2 months 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...
ICCV
2009
IEEE
15 years 14 days ago
Is that you? Metric Learning Approaches for Face Identification
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background...
Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmi...
PR
2006
164views more  PR 2006»
13 years 7 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
PAMI
2008
250views more  PAMI 2008»
13 years 7 months ago
Combined Top-Down/Bottom-Up Segmentation
We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
Eran Borenstein, Shimon Ullman
ICCV
2009
IEEE
13 years 5 months ago
Local distance functions: A taxonomy, new algorithms, and an evaluation
We present a taxonomy for local distance functions where most existing algorithms can be regarded as approximations of the geodesic distance defined by a metric tensor. We categor...
Deva Ramanan, Simon Baker