Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping

arXiv:2309.16515v2 Announce Type: replace
Abstract: Humans are able to segment images effortlessly without supervision using perceptual grouping. In this work, we propose a counter-intuitive computational approach to solving unsupervised perceptual grouping and segmentation: that they arise \textit{because} of neural noise, rather than in spite of it. We (1) mathematically demonstrate that under realistic assumptions, neural noise can be used to separate objects from each other; (2) that adding noise in a DNN enables the network to segment images even though …

abstract arxiv computational cs.cv emergence humans images leads noise segment segmentation supervision type unsupervised work