Lian Xu is a research fellow with the Department of Computer Science and Software Engineering at The University of Western Australia (UWA). She completed her PhD at UWA in 2021. Her research interests lie in a broad area of machine learning, computer vision, healthcare, smart agriculture, automatic marine monitoring and other application domains. In particular, her research has been focusing on annotation-efficient learning for scene understanding such as weakly supervised object localization and weakly supervised semantic segmentation, and multi-modal learning with vision and language data for scene understanding. She has published several works in top-tier conferences and journals in the field of Computer Vision, such as the conference on Computer Vision and Pattern Recognition (CVPR), the International Conference on Computer Vision (ICCV), IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

• Computer Vision
• Deep Learning
• Annotation-efficient learning
• Multi-modal learning
• Scene Understanding

• Feb. 2022 – Jun. 2022, facilitator, CITS4402: Computer Vision

• Feb. 2020 – Jun. 2020, facilitator, CITS2401: Computer Analysis and Visualization

• Workshop/Tutorial Co-chair,  Digital Image Computing: Techniques & Applications (DICTA 2024)
• Co-organizer, ACCV 2022 workshop on Deep Learning based Small Object Detection from Images and Videos
• Co-organizer, VCIP 2021 special session on Visual Data Classification and Analysis: In Search of the Limits of Deep Learning-based Approaches