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2024 Book Chapter MIDNet: Neural-Based Efficient Delivery of Multispectral Satellite Image DataZhang, Yiyun and Wang, Zijian (2024). MIDNet: Neural-Based Efficient Delivery of Multispectral Satellite Image Data. Lecture Notes in Computer Science. (pp. 434-446) Singapore: Springer Nature Singapore. doi: 10.1007/978-981-96-1242-0_32 |
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2024 Conference Publication Color-oriented redundancy reduction in dataset distillationYuan, Bowen, Wang, Zijian, Baktashmotlagh, Mahsa, Luo, Yadan and Huang, Zi (2024). Color-oriented redundancy reduction in dataset distillation. Thirty-eighth Annual Conference on Neural Information Processing Systems, Vancouver, BC, Canada, 10 - 15 December 2024. Maryland Heights, MO, United States: Morgan Kaufmann Publishers. |
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2024 Conference Publication CIFAR-10-Warehouse: broad and more realistic testbeds in model generalization analysisSun, Xiaoxiao, Leng, Xingjian, Wang, Zijian, Yang, Yang, Huang, Zi and Zheng, Liang (2024). CIFAR-10-Warehouse: broad and more realistic testbeds in model generalization analysis. ICLR 2024, Vienna, Austria, 7-11 May 2024. Vienna, Austria: International Conference on Learning Representations, ICLR. |
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2023 Conference Publication VLM-BCD: unsupervised building change detectionZhang, Yiyun and Wang, Zijian (2023). VLM-BCD: unsupervised building change detection. 5th ACM International Conference on Multimedia in Asia, Tainan, Taiwan, 6-8 December 2023. New York, NY, United States: ACM. doi: 10.1145/3595916.3626357 |
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2023 Conference Publication Learning efficient unsupervised satellite image-based building damage detectionZhang, Yiyun, Wang, Zijian, Luo, Yadan, Yu, Xin and Huang, Zi (2023). Learning efficient unsupervised satellite image-based building damage detection. 2023 IEEE International Conference on Data Mining (ICDM), Shanghai, China, 1-4 December 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/icdm58522.2023.00206 |
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2023 Conference Publication Towards reliable and efficient vegetation segmentation for Australian wheat data analysisYuan, Bowen, Wang, Zijian and Yu, Xin (2023). Towards reliable and efficient vegetation segmentation for Australian wheat data analysis. 34th Australasian Database Conference (ADC), Melbourne, NSW Australia, 1-3 November 2023. Cham, Switzerland: Springer Cham. doi: 10.1007/978-3-031-47843-7_9 |
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2023 Other Outputs On improving vision model transferability to address domain shift in an open worldWang, Zijian (2023). On improving vision model transferability to address domain shift in an open world. PhD Thesis, School of Electrical Engineering and Computer Science, The University of Queensland. doi: 10.14264/f619e3d |
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2023 Conference Publication How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their TransferabilityWang, Zijian, Luo, Yadan, Zheng, Liang, Huang, Zi and Baktashmotlagh, Mahsa (2023). How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00511 |
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2023 Conference Publication Exploring active 3D object detection from a generalization perspectiveLuo, Yadan, Chen, Zhuoxiao, Wang, Zijian, Yu, Xin, Huang, Zi and Baktashmotlagh, Mahsa (2023). Exploring active 3D object detection from a generalization perspective. 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, 1 - 5 May 2023. New York, NY, United States: Cornell Tech. doi: 10.48550/arXiv.2301.09249 |
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2023 Journal Article Source-free progressive graph learning for open-set domain adaptationLuo, Yadan, Wang, Zijian, Chen, Zhuoxiao, Huang, Zi and Baktashmotlagh, Mahsa (2023). Source-free progressive graph learning for open-set domain adaptation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (9), 1-16. doi: 10.1109/tpami.2023.3270288 |
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2023 Conference Publication FFM: injecting out-of-domain knowledge via factorized frequency modificationWang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2023). FFM: injecting out-of-domain knowledge via factorized frequency modification. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00412 |
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2023 Conference Publication Center-aware adversarial augmentation for single domain generalizationChen, Tianle, Baktashmotlagh, Mahsa, Wang, Zijian and Salzmann, Mathieu (2023). Center-aware adversarial augmentation for single domain generalization. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 2-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00414 |
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2022 Conference Publication FluMA: An Intelligent Platform for Influenza Monitoring and AnalysisChen, Xi, Chen, Zhi, Wang, Zijian, Qiu, Ruihong and Luo, Yadan (2022). FluMA: An Intelligent Platform for Influenza Monitoring and Analysis. 33rd Australasian Database Conference (ADC), Sydney, NSW Australia, 2-4 September 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-15512-3_12 |
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2022 Conference Publication Contrastive learning for representation degeneration problem in sequential recommendationQiu, Ruihong, Huang, Zi, Yin, Hongzhi and Wang, Zijian (2022). Contrastive learning for representation degeneration problem in sequential recommendation. WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, Virtual, AZ, United States, 21 - 25 February 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3488560.3498433 |
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2021 Conference Publication RoadAtlas: intelligent platform for automated road defect detection and asset managementChen, Zhuoxiao, Zhang, Yiyun, Luo, Yadan, Wang, Zijian, Zhong, Jinjiang and Southon, Anthony (2021). RoadAtlas: intelligent platform for automated road defect detection and asset management. MMAsia '21: ACM Multimedia Asia, Gold Coast, QLD Australia, 1 - 3 December 2021. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3469877.3493589 |
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2021 Conference Publication Learning to diversify for single domain generalizationWang, Zijian, Luo, Yadan, Qiu, Ruihong, Huang, Zi and Baktashmotlagh, Mahsa (2021). Learning to diversify for single domain generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCV48922.2021.00087 |
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2020 Conference Publication Prototype-matching graph network for heterogeneous domain adaptationWang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2020). Prototype-matching graph network for heterogeneous domain adaptation. MM '20: 28th ACM International Conference on Multimedia, Online, October 2020. New York, NY, United States: ACM. doi: 10.1145/3394171.3413662 |
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2020 Conference Publication Adversarial bipartite graph learning for video domain adaptationLuo, Yadan, Huang, Zi, Wang, Zijian, Zhang, Zheng and Baktashmotlagh, Mahsa (2020). Adversarial bipartite graph learning for video domain adaptation. ACM International Conference on Multimedia, Seattle, WA, United States, 12-16 October 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3394171.3413897 |
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2020 Journal Article Deep collaborative discrete hashing with semantic-invariant structure constructionWang, Zijian, Zhang, Zheng, Luo, Yadan, Huang, Zi and Shen, Heng Tao (2020). Deep collaborative discrete hashing with semantic-invariant structure construction. IEEE Transactions on Multimedia, 23 9096547, 1274-1286. doi: 10.1109/tmm.2020.2995267 |
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2020 Conference Publication Progressive graph learning for open-set domain adaptationLuo, Yadan, Wang, Zijian, Huang, Zi and Baktashmotlagh, Mahsa (2020). Progressive graph learning for open-set domain adaptation. 37th International Conference on Machine Learning ICML 2020, Vienna, Austria, 12-18 July 2020 . International Machine Learning Society . |
