Points2Polygons: Context-Based Segmentation from Weak Labels Using Adversarial Networks
Kuai Yu,
Hakeem Frank,
Daniel Wilson
Abstract:In applied image segmentation tasks, the ability to provide numerous and precise labels for training is paramount to the accuracy of the model at inference time. However, this overhead is often neglected, and recently proposed segmentation architectures rely heavily on the availability and fidelity of ground truth labels to achieve state-of-the-art accuracies. Failure to acknowledge the difficulty in creating adequate ground truths can lead to an over-reliance on pre-trained models or a lack of adoption in rea… Show more
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