Zhuoyue Yang

Peng Cheng Laboratory, National University of Defense Technology

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About

Zhuoyue Yang is a researcher at the forefront of computer vision and robotics, with a primary focus on simultaneous localization and mapping (SLAM) and depth estimation for medical applications. His work bridges the gap between autonomous navigation and surgical technology, addressing critical challenges in 3D reconstruction and multi-agent systems. Yang’s most impactful contribution, "Self-Supervised Lightweight Depth Estimation in Endoscopy Combining CNN and Transformer" (2024), has already garnered 40 citations, demonstrating its significance in enabling precise 3D reconstruction for surgical navigation and robotic assistance without requiring ground-truth data. This work innovatively fuses convolutional neural networks with transformer architectures to achieve robust, lightweight depth prediction in complex endoscopic environments. Earlier, Yang contributed foundational reviews and collaborative frameworks in SLAM, including "Mapping Technology in Visual SLAM" (2018) and "Multi-UAV Collaborative Monocular SLAM Focusing on Data Sharing" (2018), which collectively highlight his expertise in map construction and data-sharing strategies for unmanned aerial vehicles. His research not only advances autonomous systems but also has direct translational impact on medical engineering, making him a notable figure in applied computer vision.