Image Segmentation by Iterative Inference from Conditional Score Estimation

ICLR 2018 Adriana RomeroMichal DrozdzalAkram ErraqabiSimon JégouYoshua Bengio

Inspired by the combination of feedforward and iterative computations in the virtual cortex, and taking advantage of the ability of denoising autoencoders to estimate the score of a joint distribution, we propose a novel approach to iterative inference for capturing and exploiting the complex joint distribution of output variables conditioned on some input variables. This approach is applied to image pixel-wise segmentation, with the estimated conditional score used to perform gradient ascent towards a mode of the estimated conditional distribution... (read more)

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