Yiming Wan

Institute of Automation, Huazhong University of Science and Technology

Papers

Total Citations

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About

Yiming Wan is a researcher at the intersection of computer vision, robotics, and telerobotic systems, with a primary focus on visual localization and environmental interaction control. Their most impactful work addresses the fundamental challenge of appearance changes in visual localization—a critical problem for autonomous navigation over large time spans. In their 2020 paper "Boosting Image-Based Localization Via Randomly Geometric Data Augmentation" (5 citations), Wan introduced innovative data augmentation techniques to improve deep learning-based monocular pose regression, enhancing robustness against environmental variations. This work was complemented by "Scene-Unified Image Translation For Visual Localization" (3 citations), which tackled domain gaps between query and database images. Demonstrating versatility, Wan's 2025 paper "Scaled non-passive environmental interaction force tracking for telerobotic manufacturing system with variable time delay" (3 citations) extends their expertise into telerobotics, addressing force tracking stability under communication delays—a critical challenge for remote manufacturing. With a growing citation footprint, Wan's contributions span from foundational visual localization methods to practical robotic control systems, showcasing a rare ability to bridge perception and manipulation. Their work continues to influence both academic research and real-world robotic applications.