Honglin Yuan

Nanjing University of Information Science and Technology, Utrecht University

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About

Honglin Yuan is a researcher advancing the fields of 3D computer vision and robotics, with a primary focus on 6D object pose estimation and 3D scene understanding. Yuan’s major contributions include developing novel deep learning architectures that fuse color and geometric features to robustly estimate object poses under challenging conditions such as heavy occlusion, changing illumination, and cluttered environments. This work, published in 2020, laid the foundation for subsequent research and applications in robotic grasping, virtual reality, and visual navigation. Yuan also played a key role in organizing and contributing to the SHREC 2020 and 2023 tracks, notably introducing a benchmark for point cloud change detection in city scenes—a critical task for autonomous driving and urban monitoring. Additionally, Yuan contributed to the creation of RobotP, a benchmark dataset for 6D object pose estimation that addresses the difficulty of collecting large, representative training sets for robotic vision. With over 25 citations across key publications, Yuan’s work is shaping the next generation of perception systems for robotics and augmented reality, bridging the gap between deep learning research and real-world deployment.