Uncertainty and Self-Supervision in Single-View Depth

arXiv:2406.14226v1 Announce Type: new
Abstract: Single-view depth estimation refers to the ability to derive three-dimensional information per pixel from a single two-dimensional image. Single-view depth estimation is an ill-posed problem because there are multiple depth solutions that explain 3D geometry from a single view. While deep neural networks have been shown to be effective at capturing depth from a single view, the majority of current methodologies are deterministic in nature. Accounting for uncertainty in the predictions can avoid disastrous consequences …

abstract arxiv cs.cv geometry image information multiple networks neural networks per pixel problem solutions supervision three-dimensional type uncertainty view while