Weihao Li

Dr. Weihao Li is a Research Fellow at The Australian National University's School of Computing, specializing in computer vision and machine learning. His research focuses on object detection, image segmentation, open-set recognition, and point cloud segmentation. He holds a Dr. rer. nat. (PhD equivalent) and is registered to supervise research students.

His research interests revolve around advancing techniques for dynamic instance segmentation, open-set learning, and 3D point cloud analysis. Notable projects include the ANU bushfire smoke dataset and contributions to generalized semantic segmentation and anomaly recognition. His work emphasizes data augmentation strategies and weakly-supervised learning methods.

Key technical areas include synthetic dynamic instance copy-paste for video segmentation, curved geometric networks for anomaly detection, and cross-modal fusion in building facade analysis. He collaborates on computing-for-social-good initiatives, such as environmental monitoring via hyperspectral imaging.

Dr. Li's publications span 2016–2024, with a focus on advancing computer vision through innovative architectures and methodologies. His recent work explores open-set recognition, few-shot learning with reinforced attention, and geometric prior-based segmentation techniques.