Depth Estimation

Depth estimation is a task in computer vision that aims to measure the distance of each pixel relative to the camera. This task extracts depth information from monocular or stereo images, with traditional methods based on multi-view geometry, while newer methods directly estimate depth by minimizing regression loss or learning to generate new views from sequences. Depth estimation has significant application value in areas such as autonomous driving, robot navigation, and augmented reality, with common evaluation metrics including Root Mean Square Error (RMS), and major benchmark datasets including KITTI and NYUv2.