Monocular Image

Monocular image analysis focuses on extracting three-dimensional information and understanding from a single two-dimensional image, a challenging problem with broad applications. Current research heavily utilizes deep learning, employing various neural network architectures like transformers and convolutional neural networks, often incorporating techniques such as self-supervised learning and data augmentation to improve accuracy and robustness. These advancements are driving progress in diverse fields, including autonomous navigation, robotics, 3D modeling, and medical imaging, by enabling efficient and cost-effective 3D scene understanding and object manipulation. The ability to accurately interpret depth, pose, and other geometric properties from a single image is significantly impacting the feasibility and performance of numerous applications.