I am a Lecturer (Assistant Professor) at School of Physics, Mathematics and Computing, The University of Western Australia. I was a postdoctoral researcher in A/Prof Chang Xu’s group at the School of Computer Science, The University of Sydney. I obtained a PhD degree from Peking University supervised by A/Prof Tingting Jiang and Prof Yizhou Wang. My research interests lie in generative artificial intelligence, computer vision, human action and skill understanding, also with interdisciplinary applications in healthcare data science.
I am actively looking for PhD/MPhil/Visiting students and research interns. If you are interested in working with me, please feel free to contact me.
📝 Generative Artificial Intelligence
Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
Xiyu Wang, Baijiong Lin, Daochang Liu, Ying-Cong Chen, Chang Xu
International Conference on Machine Learning (ICML), 2024
Towards Memorization-Free Diffusion Models
Chen Chen, Daochang Liu, Chang Xu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Rethinking Conditional Diffusion Sampling with Progressive Guidance
Anh-Dung Dinh, Daochang Liu, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2023
Contrastive Sampling Chains in Diffusion Models
Junyu Zhang,Daochang Liu, Shichao Zhang, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2023
PixelAsParam: A Gradient View on Diffusion Sampling with Guidance
Anh-Dung Dinh, Daochang Liu, Chang Xu
International Conference on Machine Learning (ICML), 2023
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Residual Learning in Diffusion Models, Junyu Zhang, Daochang Liu, Eunbyung Park, Shichao Zhang, Chang Xu. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
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Boosting Diffusion Models with an Adaptive Momentum Sampler , Xiyu Wang, Anh-Dung Dinh, Daochang Liu, Chang Xu. International Joint Conference on Artificial Intelligence (IJCAI), 2024
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Personalized Image Generation for Color Vision Deficiency Population , Shuyi Jiang, Daochang Liu, Dingquan Li, Chang Xu. International Conference on Computer Vision (ICCV), 2023, [Code]
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Private Image Generation with Dual-Purpose Auxiliary Classifier , Chen Chen, Daochang Liu, Siqi Ma, Surya Nepal, Chang Xu. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 [Code] [Video]
📝 Computer Vision and Human Action Understanding
Daochang Liu, Qiyue Li, Anh-Dung Dinh, Tingting Jiang, Mubarak Shah, Chang Xu
International Conference on Computer Vision (ICCV), 2023
Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization
Daochang Liu, Tingting Jiang, Yizhou Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Contrastive Code-Comment Pre-training
Xiaohuan Pei, Daochang Liu, Qian Luo, Chang Xu
IEEE International Conference on Data Mining (ICDM), 2022
Best Student Paper Award
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Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense, Zunzhi You, Daochang Liu, Chang Xu. Conference on Neural Information Processing Systems (NeurIPS), 2023, [Code]
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Learning Spatiotemporal Frequency-Transformer for Low-Quality Video Super-Resolution, Zhongwei Qiu, Huan Yang, Jianlong Fu, Daochang Liu, Chang Xu, Dongmei Fu. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, [Code]
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Calibrating a Deep Neural Network with Its Predecessors, Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu. International Joint Conference on Artificial Intelligence (IJCAI), 2023, [Code] [Playground]
📝 AI for Healthcare and Surgery
Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion
Daochang Liu*, Yuhui Wei*, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020
Clearness of Operating Field: A Surrogate for Surgical Skills on In-Vivo Clinical Data
Daochang Liu, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li
International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2020
Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field
Daochang Liu, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification
Daochang Liu, Tingting Jiang
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
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Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark, Martin Wagner, …, Daochang Liu, …, Sebastian Bodenstedt. Medical Image Analysis (MedIA), 2023, [Dataset]
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Surgical Skill Assessment Method and Device, Tingting Jiang, Ziyu Li, Daochang Liu, Qiyue Li, Yizhou Wang, Rulin Miao, Fei Shan. China Patent (ZL202110443748.9)
♥️ Services
- 2024, Chair of The 1st Workshop on Efficiency, Security, and Generalization of Multimedia Foundation Models at ACM MM 2024
- 2024, Area Chair of International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
- 2024, Co-Chair of IJCNN 2024 Special Session “Efficiency, Security, and Generalization of Foundation Models”
- 2023, Co-Organizer of Coding Fest USYD & Macquarie Workshop
- 2022, Local Arrangement Chair and Session Chair of The International Conference on Digital Image Computing: Techniques and Applications (DICTA)
- Program Committee Member of CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, MICCAI, ACM MM, BMVC, AAAI, IJCAI, KDD, ICDM, DICTA
- Reviewer of TPAMI, TMI, TMM, TCSVT, TNNLS, CVIU, TMLR, Pattern Recognition, IEEE Access
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Contact: daochang.liu at sydney.edu.au, finspire13 at gmail.com
Last Update: Nov 04, 2024