Imperial College London Researchers Propose A Novel Randomly Connected Neural Network For Self-Supervised Monocular Depth Estimation In Computer Vision

Depth estimation is one of the fundamental problems in computer vision, and it's essential for a wide range of applications, such as robotic vision or surgical navigation. Various deep learning-based approaches have been developed to provide end-to-end solutions for depth and disparity estimation in recent times. One such method is self-supervised monocular depth estimation. Monocular depth estimation is the process of determining scene depth from a single image. For disparity estimation, the bulk of these models use a U-Net-based design.