Weakly Supervised Object Co-Localization via Sharing Parts Based on a Joint Bayesian Model
نویسندگان
چکیده
منابع مشابه
Bayesian learning for weakly supervised object classification
We explore the extent to which we can exploit interest point detectors for representing and recognising classes of objects. Detectors propose sparse sets of candidate regions based on local salience and stability criteria. However, local selection does not take into account discrimination reliability across instances in the same object class, so we realise selection by learning from weakly supe...
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Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learning object classifiers from weakly labeled image data, where only the presence of an object in an image is known, but not its location. Some recent work has explored the application of MIL algorithms to the tasks of im...
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ژورنال
عنوان ژورنال: Symmetry
سال: 2018
ISSN: 2073-8994
DOI: 10.3390/sym10050142