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Instance Separation Emerges from Inpainting
[article]
2020
arXiv
pre-print
Deep neural networks trained to inpaint partially occluded images show a deep understanding of image composition and have even been shown to remove objects from images convincingly. In this work, we investigate how this implicit knowledge of image composition can be leveraged for fully self-supervised instance separation. We propose a measure for the independence of two image regions given a fully self-supervised inpainting network and separate objects by maximizing this independence. We
arXiv:2003.00891v1
fatcat:ew5pl7ty6jeo3f74alpr5ltj4u