Model-based occlusion disentanglement for image-to-image translation

2 Apr 2020Fabio PizzatiPietro CerriRaoul de Charette

Image-to-image translation is affected by entanglement phenomena, which may occur in case of target data encompassing occlusions such as raindrops, dirt, etc. Our unsupervised model-based learning disentangles scene and occlusions, while benefiting from an adversarial pipeline to regress physical parameters of the occlusion model... (read more)

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