Daochang Liu

According to our database, Daochang Liu authored at least 23 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Collage Prompting: Budget-Friendly Visual Recognition with GPT-4V.

Siyu Xu, Yunke Wang, Daochang Liu, Chang Xu

CoRR, 2024

2023

Learning Degradation-Robust Spatiotemporal Frequency-Transformer for Video Super-Resolution.

Zhongwei Qiu, Huan Yang, Jianlong Fu, Daochang Liu, Chang Xu, Dongmei Fu

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark.

Martin Wagner, Beat P. Müller-Stich, Anna Kisilenko, Duc Tran, Patrick Heger, Lars Mündermann, David M. Lubotsky, Benjamin Müller, Tornike Davitashvili, Manuela Capek, Annika Reinke, Carissa Reid, Tong Yu, Armine Vardazaryan, Chinedu Innocent Nwoye, Nicolas Padoy, Xinyang Liu, Eung-Joo Lee, Constantin Disch, Hans Meine, Tong Xia, Fucang Jia, Satoshi Kondo, Wolfgang Reiter, Yueming Jin, Yonghao Long, Meirui Jiang, Qi Dou, Pheng-Ann Heng, Isabell Twick, Kadir Kirtaç, Enes Hosgor, Jon Lindström Bolmgren, Michael Stenzel, Björn von Siemens, Long Zhao, Zhenxiao Ge, Haiming Sun, Di Xie, Mengqi Guo, Daochang Liu, Hannes Götz Kenngott, Felix Nickel, Moritz von Frankenberg, Franziska Mathis-Ullrich, Annette Kopp-Schneider, Lena Maier-Hein, Stefanie Speidel, Sebastian Bodenstedt

Medical Image Anal., May, 2023

Efficient Transfer Learning in Diffusion Models via Adversarial Noise.

Xiyu Wang, Baijiong Lin, Daochang Liu, Chang Xu

CoRR, 2023

Boosting Diffusion Models with an Adaptive Momentum Sampler.

Xiyu Wang, Anh-Dung Dinh, Daochang Liu, Chang Xu

CoRR, 2023

Two-in-one Knowledge Distillation for Efficient Facial Forgery Detection.

Chuyang Zhou, Jiajun Huang, Daochang Liu, Chengbin Du, Siqi Ma, Surya Nepal, Chang Xu

CoRR, 2023

Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense.

Zunzhi You, Daochang Liu, Chang Xu

CoRR, 2023

Contrastive Sampling Chains in Diffusion Models.

Junyu Zhang, Daochang Liu, Shichao Zhang, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense.

Zunzhi You, Daochang Liu, Bohyung Han, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rethinking Conditional Diffusion Sampling with Progressive Guidance.

Anh-Dung Dinh, Daochang Liu, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Calibrating a Deep Neural Network with Its Predecessors.

Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

PixelAsParam: A Gradient View on Diffusion Sampling with Guidance.

AnhDung Dinh, Daochang Liu, Chang Xu

Proceedings of the International Conference on Machine Learning, 2023

Diffusion Action Segmentation.

Daochang Liu, Qiyue Li, Anh-Dung Dinh, Tingting Jiang, Mubarak Shah, Chang Xu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Personalized Image Generation for Color Vision Deficiency Population.

Shuyi Jiang, Daochang Liu, Dingquan Li, Chang Xu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Private Image Generation with Dual-Purpose Auxiliary Classifier.

Chen Chen, Daochang Liu, Siqi Ma, Surya Nepal, Chang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Learning Spatiotemporal Frequency-Transformer for Low-Quality Video Super-Resolution.

Zhongwei Qiu, Huan Yang, Jianlong Fu, Daochang Liu, Chang Xu, Dongmei Fu

CoRR, 2022

Contrastive Code-Comment Pre-training.

Xiaohuan Pei, Daochang Liu, Luo Qian, Chang Xu

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

Towards Unified Surgical Skill Assessment.

Daochang Liu, Qiyue Li, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

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

Int. J. Comput. Assist. Radiol. Surg., 2020

Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion.

Daochang Liu, Yuhui Wei, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization.

Daochang Liu, Tingting Jiang, Yizhou Wang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification.

Daochang Liu, Tingting Jiang

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018