M. Salman Asif

Papers

Total Citations

156

H-Index

About

M. Salman Asif is a leading researcher in computer vision and deep learning, with a primary focus on depth estimation and its applications in robotics and autonomous systems. His most-cited work, the 2022 review "Monocular Depth Estimation Using Deep Learning: A Review," has garnered 156 citations, establishing itself as a foundational reference in the field. This comprehensive survey systematically categorizes and evaluates deep learning approaches for predicting depth from single images, addressing critical challenges in 3D scene understanding. Asif's contributions extend beyond surveys; his research advances monocular depth estimation techniques that enable robots and autonomous vehicles to perceive their environments with greater accuracy and efficiency. By synthesizing decades of progress and identifying key methodological trends, his work has guided subsequent innovations in self-supervised learning, multi-task architectures, and real-time depth prediction. With over 150 citations on this seminal paper alone, Asif's scholarship continues to shape the trajectory of computer vision research, providing both newcomers and experts with a clear roadmap of the field's evolution and future directions.