Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation

We consider the task of learning a classifier for semantic segmentation using weak supervision in the form of image labels which specify the object classes present in the image. Our method uses deep convolutional neural networks (CNNs) and adopts an Expectation-Maximization (EM) based approach... (read more)

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METHOD TYPE
Softmax
Output Functions