Yan Mi

About

Yan Mi is a researcher at the forefront of 3D computer vision, with a primary focus on point cloud processing and domain adaptation. Their most significant contribution is the development of geometry-aware implicit representations to address a critical challenge in the field: the geometric variations that occur when the same object is captured by different sensors or under varying conditions. In their highly cited 2022 work, "Domain Adaptation on Point Clouds via Geometry-Aware Implicits," Mi introduced a novel framework that leverages implicit functions to learn robust, geometry-aware features, enabling models to generalize across different point cloud domains. This work has garnered 64 citations, underscoring its impact on the community. By tackling the unsolved issue of domain shift in 3D data, Mi’s research has direct implications for real-world applications in autonomous driving and robotics, where reliable perception across diverse environments is critical. Their work represents a key step toward more adaptable and resilient 3D vision systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Domain Adaptation on Point Clouds via Geometry-Aware Implicits

   64 citations · 2022
2. 2
   Domain Adaptation on Point Clouds via Geometry-Aware Implicits

   2 citations · 2021

Key Collaborators

Contact & Links