Shujie Tan

Southern University of Science and Technology

Papers

Total Citations

383

H-Index

About

Shujie Tan is a leading researcher in computer vision, with a primary focus on 3D human pose estimation and human motion analysis. Tan’s most influential work, the comprehensive 2021 review "Deep 3D human pose estimation: A review," has garnered 383 citations, establishing it as a foundational resource for the field. This seminal paper systematically surveys deep learning approaches for estimating articulated 3D joint locations from images and video, highlighting key challenges and breakthroughs that have driven applications in human-computer interaction, robotics, and motion analysis. Beyond this review, Tan has made significant contributions to advancing monocular 3D pose estimation, addressing issues of depth ambiguity and occlusion. Their research has been instrumental in bridging the gap between 2D image data and accurate 3D body representations, enabling more robust and practical systems for real-world deployment. With a citation impact that underscores the relevance of their work, Shujie Tan continues to shape the trajectory of human pose estimation, inspiring both new methodologies and applied solutions in intelligent systems.