Metric Depth Estimation

Metric depth estimation aims to recover accurate, real-world distances from single images, a challenging problem due to the inherent scale ambiguity in perspective projection. Current research focuses on improving the generalization of monocular depth estimation models across diverse scenes and camera parameters, employing techniques like incorporating language descriptions, robot kinematics, and diffusion models to resolve scale inconsistencies. These advancements are crucial for various applications, including robotics, autonomous driving, and augmented reality, where precise depth information is essential for accurate scene understanding and interaction.