3 code implementations • ICCV 2021 • Elias Kassapis, Georgi Dikov, Deepak K. Gupta, Cedric Nugteren
To this end, we propose a novel two-stage, cascaded approach for calibrated adversarial refinement: (i) a standard segmentation network is trained with categorical cross entropy to predict a pixelwise probability distribution over semantic classes and (ii) an adversarially trained stochastic network is used to model the inter-pixel correlations to refine the output of the first network into coherent samples.