A sparse object category model for efficient learning and exhaustive recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semi-supervised manner: the model is learnt from example images containing category instances, without requiring segmentation from background clutter. The model is a sparse repr...
| Main Authors: | , , |
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| 格式: | Conference item |
| 語言: | English |
| 出版: |
IEEE
2005
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