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.
📝 Research
[23] DiffAct++: Diffusion Action Segmentation
Daochang Liu, Qiyue Li, Anh-Dung Dinh, Tingting Jiang, Mubarak Shah, Chang Xu
IEEE Transactions on Pattern Analysis & Machine Intelligence (TPAMI)
[22] Towards Memorization-Free Diffusion Models
Chen Chen, Daochang Liu, Chang Xu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[21] 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
[20] 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
[19] 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
[18] Diffusion Action Segmentation
Daochang Liu, Qiyue Li, Anh-Dung Dinh, Tingting Jiang, Mubarak Shah, Chang Xu
International Conference on Computer Vision (ICCV), 2023
[17] Rethinking Conditional Diffusion Sampling with Progressive Guidance
Anh-Dung Dinh, Daochang Liu, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2023
[16] Contrastive Sampling Chains in Diffusion Models
Junyu Zhang,Daochang Liu, Shichao Zhang, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2023
[15] Personalized Image Generation for Color Vision Deficiency Population
Shuyi Jiang, Daochang Liu, Dingquan Li, Chang Xu
International Conference on Computer Vision (ICCV), 2023
[14] PixelAsParam: A Gradient View on Diffusion Sampling with Guidance
Anh-Dung Dinh, Daochang Liu, Chang Xu
International Conference on Machine Learning (ICML), 2023
[13] 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
[12] 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
[10] 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
[9] 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
[8] 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
[7] 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
[6] 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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[5] 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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[4] 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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[3] 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]
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[2] 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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[1] 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 IJCV, 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