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Deep Imbalanced Attribute Classification Using Visual Attention Aggregation
[chapter]
2018
Lecture Notes in Computer Science
For many computer vision applications, such as image description and human identification, recognizing the visual attributes of humans is an essential yet challenging problem. Its challenges originate from its multi-label nature, the large underlying class imbalance and the lack of spatial annotations. Existing methods follow either a computer vision approach while failing to account for class imbalance, or explore machine learning solutions, which disregard the spatial and semantic relations
doi:10.1007/978-3-030-01252-6_42
fatcat:jft7ls2jxvhuflyczq7c6dhzgu