Shaorong Wang is an Associate Professor and master’s supervisor at the School of Information Science and Technology, School of Artificial Intelligence, Beijing Forestry University. He received his bachelor’s degree in mathematics from Nanjing University and his PhD in computer application technology from the Institute of Computing Technology, Chinese Academy of Sciences, and completed postdoctoral research at Peking University.
His research focuses on machine learning, 3D reconstruction, embodied intelligence, and computer vision. He has led and contributed to projects funded by the National Key R&D Program of China and the National Natural Science Foundation of China, as well as the development of flight simulation visual systems, virtual battlefields, and digital ocean systems. This work received a First Prize for Scientific and Technological Progress from the Ministry of Education. He has published more than 40 papers, including work presented at CVPR. He was recognized as an Outstanding Reviewer at the 16th National Conference on Geometric Design and Computing and as an Outstanding Undergraduate Thesis Supervisor in Beijing.
A generalized few-shot semantic segmentation method combining contrastive learning and orthogonal decoupling (CCF C), recommended by ChinaMM 2025.
A generalized few-shot semantic segmentation method based on relevant intrinsic feature enhancement (CCF C).
A geometry-adaptive propagated transformer for point cloud representation (CCF C).
A method for disentangling changes and invariants in multi-period scenes, accepted by CVPR 2026 (CCF A).
Temporal modeling of predictive gaze stabilization for augmented reality interaction.
An asymmetric dual-stream lightweight network for RGB-D salient object detection, recommended by CCF CAD/CG 2024.