Hanshu Yan

According to our database, Hanshu Yan authored at least 33 papers between 2019 and 2024.

Collaborative distances:

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

2024

Learning a robust foundation model against clean-label data poisoning attacks at downstream tasks.

Ting Zhou, Hanshu Yan, Bo Han, Lei Liu, Jingfeng Zhang

Neural Networks, January, 2024

OFTSR: One-Step Flow for Image Super-Resolution with Tunable Fidelity-Realism Trade-offs.

Yuanzhi Zhu, Ruiqing Wang, Shilin Lu, Junnan Li, Hanshu Yan, Kai Zhang

CoRR, 2024

Accelerating Video Diffusion Models via Distribution Matching.

Yuanzhi Zhu, Hanshu Yan, Huan Yang, Kai Zhang, Junnan Li

CoRR, 2024

DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention.

Lianghui Zhu, Zilong Huang, Bencheng Liao, Jun Hao Liew, Hanshu Yan, Jiashi Feng, Xinggang Wang

CoRR, 2024

ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance.

Jiannan Huang, Jun Hao Liew, Hanshu Yan, Yuyang Yin, Yao Zhao, Yunchao Wei

CoRR, 2024

InstaDrag: Lightning Fast and Accurate Drag-based Image Editing Emerging from Videos.

Yujun Shi, Jun Hao Liew, Hanshu Yan, Vincent Y. F. Tan, Jiashi Feng

CoRR, 2024

PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator.

Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, Jiashi Feng

CoRR, 2024

MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation.

Weimin Wang, Jiawei Liu, Zhijie Lin, Jiangqiao Yan, Shuo Chen, Chetwin Low, Tuyen Hoang, Jie Wu, Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng

CoRR, 2024

AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models.

Jiachun Pan, Jun Hao Liew, Vincent Y. F. Tan, Jiashi Feng, Hanshu Yan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach.

Xiang Lan, Hanshu Yan, Shenda Hong, Mengling Feng

Proceedings of the Twelfth International Conference on Learning Representations, 2024

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model.

Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew, Hanshu Yan, Jia-Wei Liu, Chenxu Zhang, Jiashi Feng, Mike Zheng Shou

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

DragDiffusion: Harnessing Diffusion Models for Interactive Point-Based Image Editing.

Yujun Shi, Chuhui Xue, Jun Hao Liew, Jiachun Pan, Hanshu Yan, Wenqing Zhang, Vincent Y. F. Tan, Song Bai

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Towards Accurate Guided Diffusion Sampling through Symplectic Adjoint Method.

Jiachun Pan, Hanshu Yan, Jun Hao Liew, Jiashi Feng, Vincent Y. F. Tan

CoRR, 2023

MagicProp: Diffusion-based Video Editing via Motion-aware Appearance Propagation.

Hanshu Yan, Jun Hao Liew, Long Mai, Shanchuan Lin, Jiashi Feng

CoRR, 2023

MagicEdit: High-Fidelity and Temporally Coherent Video Editing.

Jun Hao Liew, Hanshu Yan, Jianfeng Zhang, Zhongcong Xu, Jiashi Feng

CoRR, 2023

MagicAvatar: Multimodal Avatar Generation and Animation.

Jianfeng Zhang, Hanshu Yan, Zhongcong Xu, Jiashi Feng, Jun Hao Liew

CoRR, 2023

Towards Better Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach.

Xiang Lan, Hanshu Yan, Shenda Hong, Mengling Feng

CoRR, 2023

2022

Information-Theoretic Characterization of the Generalization Error for Iterative Semi-Supervised Learning.

Haiyun He, Hanshu Yan, Vincent Y. F. Tan

J. Mach. Learn. Res., 2022

MagicVideo: Efficient Video Generation With Latent Diffusion Models.

Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv, Yizhe Zhu, Jiashi Feng

CoRR, 2022

Towards Adversarial Robustness of Deep Vision Algorithms.

Hanshu Yan

CoRR, 2022

MagicMix: Semantic Mixing with Diffusion Models.

Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng

CoRR, 2022

Towards Adversarially Robust Deep Image Denoising.

Hanshu Yan, Jingfeng Zhang, Jiashi Feng, Masashi Sugiyama, Vincent Y. F. Tan

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Efficient Sharpness-aware Minimization for Improved Training of Neural Networks.

Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, Vincent Y. F. Tan

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Adversarial Domain Adaptation With Prototype-Based Normalized Output Conditioner.

Dapeng Hu, Jian Liang, Qibin Hou, Hanshu Yan, Yunpeng Chen

IEEE Trans. Image Process., 2021

Information-Theoretic Generalization Bounds for Iterative Semi-Supervised Learning.

Haiyun He, Hanshu Yan, Vincent Y. F. Tan

CoRR, 2021

Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond.

Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Recovering the Unbiased Scene Graphs from the Biased Ones.

Meng-Jiun Chiou, Henghui Ding, Hanshu Yan, Changhu Wang, Roger Zimmermann, Jiashi Feng

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Modeling Trajectories with Neural Ordinary Differential Equations.

Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection.

Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

RAIN: Robust and Accurate Classification Networks with Randomization and Enhancement.

Jiawei Du, Hanshu Yan, Joey Tianyi Zhou, Rick Siow Mong Goh, Jiashi Feng

CoRR, 2020

PANDA: Prototypical Unsupervised Domain Adaptation.

Dapeng Hu, Jian Liang, Qibin Hou, Hanshu Yan, Yunpeng Chen, Shuicheng Yan, Jiashi Feng

CoRR, 2020

On Robustness of Neural Ordinary Differential Equations.

Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, Jiashi Feng

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Unsupervised Image Noise Modeling with Self-Consistent GAN.

Hanshu Yan, Vincent Y. F. Tan, Wenhan Yang, Jiashi Feng

CoRR, 2019