Xiaohan Yu Homepage

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Bio

Dr Xiaohan Yu took up the role of Lecturer in Artificial Intelligence (AI) at Macquarie University’s School of Computing in December 2023. Before that, he completed his doctoral studies at Griffith University, Australia, and joined as a Research Fellow the ARC Research Hub for Driving Farming Productivity and Disease Prevention (Griffith University). He received the APRS (Australian Pattern Recognition Society) ECR Award 2022 for his contribution in bridging pattern recognition and smart farming. Dr Yu’s research interests include Ultra-Fine-Grained Visual Categorization (Ultra-FGVC), Smart Farming, and Automated Crop Cultivar Identification. He established and pushed forward the research progress of Ultra-FGVC, and authored over 50 (18 with CORE A* ranking) publications in reputable conferences and journals including ICCV, CVPR, ECCV, AAAI, IJCAI, Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems for Video Technology, etc. He is the Associate Editor of journal Pattern Recognition and SN Computer Science, and Area Chair for ACM MM 2024..

Selective Publications

♦ Yu, X., Wang, J., Gao, Y. (2023). CLE-ViT: Contrastive Learning Encoded Transformer for Ultra-FGVC. In IJCAI. · Paper Link · Code

♦ Yu, X., Wang, J., Zhao, Y., Gao, Y. (2022). Mix-ViT: Mixing Attentive Vision Transformer for Ultra-FGVC. In Pattern Recognition. · Paper Link · Code

♦ Yu, X., Gao, Y., Bennamoun, M., Xiong, S. (2022). A Lie Algebra Representation for Efficient Curved Shape Classification. In Pattern Recognition. · Paper Link · Code

♦ Yu, X., Zhao, Y., Gao, Y. (2022). SPARE: Self-Supervised Part Erasing for Ultra-Fine-Grained Visual Categorization. In Pattern Recognition. · Paper Link · Code

♦ Zhao, Y., Yu, X., Gao, Y., Shen, C. (2021). Learning discriminative region representation for person retrieval. In Pattern Recognition. · Paper Link · Code

♦ Yu, X., Zhao, Y., Gao, Y., Xiong, S., & Yuan, X. (2021). Benchmark Platform for Ultra-Fine-Grained Visual Categorization Beyond Human Performance In ICCV. · Paper Link · Dataset

♦ Yu, X., Zhao, Y., Gao, Y., & Xiong, S. (2021). MaskCOV: A Random Mask Covariance Network for Ultra-Fine-Grained Visual Categorization. In Pattern Recognition. · Paper Link · Code

♦ Zhao, Y., Shen, C., Yu, X., Chen, H., Gao, Y., & Xiong. S. (2021). Learning deep part-aware embedding for person retrieval. In Pattern Recognition. · Paper Link · Code

♦ Yu, X., Zhao, Y., Gao, Y., Xiong, S., & Yuan, X. (2020). Patchy Image Structure Classification Using Multi-Orientation Region Transform. In AAAI. · Paper Link · Code