Depth Network

Depth networks are artificial neural networks designed to estimate depth information from images or other sensor data, aiming to improve 3D scene understanding and object detection. Current research focuses on enhancing accuracy and efficiency, particularly in challenging scenarios like low-texture regions or sparse views, employing various architectures including convolutional neural networks (CNNs), transformers, and diffusion models, often incorporating techniques like multi-scale feature extraction, depth supervision, and uncertainty estimation. These advancements have significant implications for applications such as autonomous driving, robotics, augmented reality, and medical image analysis, enabling more robust and accurate 3D perception in diverse environments.