Baoli Lu

Institute of Semiconductors, Chinese Academy of Sciences

Papers

Total Citations

228

H-Index

About

Baoli Lu is a rising researcher at the forefront of computer vision and multimodal robotics, whose work bridges deep learning, 3D perception, and intelligent robotic systems. Lu’s most impactful contribution is the comprehensive survey, "Deep learning-based 3D point cloud classification: A systematic survey and outlook," which has garnered 196 citations, establishing it as a key reference for researchers navigating the rapidly evolving field of 3D point cloud analysis. This work systematically categorizes deep learning approaches, identifies critical challenges, and outlines future directions, making it an essential resource for advancing autonomous navigation and scene understanding. In parallel, Lu has advanced multimodal robotics with "YOLOv8-PoseBoost: Advancements in Multimodal Robot Pose Keypoint Detection" (21 citations), which enhances motion keypoint detection in complex environments, addressing limitations in small target and occluded scenarios. Additionally, Lu’s earlier work on stereo disparity optimization for continuous video (11 citations) demonstrates a sustained focus on depth perception. With a growing citation impact and a clear trajectory toward solving real-world perception challenges, Baoli Lu is a promising voice in the integration of deep learning and robotics.