Weakly Supervised Image Classification Through Noise Regularization

CVPR 2019 Mengying Hu Hu Han Shiguang Shan Xilin Chen

Weakly supervised learning is an essential problem in computer vision tasks, such as image classification, object recognition, etc., because it is expected to work in the scenarios where a large dataset with clean labels is not available. While there are a number of studies on weakly supervised image classification, they usually limited to either single-label or multi-label scenarios... (read more)

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