Camera Pose

Camera pose estimation, determining a camera's 3D position and orientation from images, is crucial for numerous computer vision applications, including 3D reconstruction, robotics, and augmented reality. Current research emphasizes robust methods that handle challenges like sparse views, ambiguous scenes, and noisy data, often employing neural networks (e.g., NeRFs, transformers) and probabilistic approaches to address multi-modal pose distributions. These advancements improve the accuracy and efficiency of pose estimation, enabling more reliable and versatile applications across various fields.