Zengzhen Mi

Chongqing University of Science and Technology

Papers

Total Citations

H-Index

About

Zengzhen Mi is an emerging researcher in the field of computer vision and robotics, with a focus on simultaneous localization and mapping (SLAM) technologies. Their work addresses one of the most challenging frontiers in autonomous systems: enabling robust visual SLAM performance in highly dynamic real-world environments. Traditional SLAM systems often struggle when scenes contain moving objects — such as pedestrians or vehicles — that violate the static-world assumption. Mi's research tackles this critical limitation by integrating dense map reconstruction capabilities alongside dynamic object handling, pushing the boundaries of what autonomous agents can perceive and navigate. Their most notable publication, "Visual SLAM and Dense Map Reconstruction in Highly Dynamic Environments" (2025), has already begun attracting attention from the robotics and computer vision communities, accumulating citations shortly after its release — a promising indicator of its relevance to ongoing research challenges. As autonomous vehicles, drones, and service robots increasingly operate in unpredictable human environments, Mi's contributions stand to have meaningful real-world impact. Their trajectory suggests a researcher poised to make significant long-term contributions to intelligent perception and scene understanding.