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- W2079632337 abstract "Scene recognition is an important task for many computer vision and robotics applications. Recent progress in high-level object-based image representation has shown superior performance on scene classification tasks. In this work, we make an observation that groups of objects tend to co-occur frequently in a scene. We therefore propose to a novel framework that automatically learns object groups, and use them to build an image representation for scene recognition tasks. We model each object group as a template that explicitly encodes the spatial configurations of objects. To encourage the informativeness and discriminability, we learn the object group templates in a sparse filtering framework. Experiment results show that our object group representation could achieve state-of-the-art performance for both scene discovery and scene classification tasks." @default.
- W2079632337 created "2016-06-24" @default.
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- W2079632337 date "2014-07-01" @default.
- W2079632337 modified "2023-09-27" @default.
- W2079632337 title "Learning Object Groups for Scene Recognition" @default.
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- W2079632337 doi "https://doi.org/10.4028/www.scientific.net/amr.998-999.1028" @default.
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