102 citations · 194 across the 9 of their papers we have counts for
10 papers
Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction
Bingyu Xin, Meng Ye, Leon Axel +1
The key to dynamic or multi-contrast magnetic resonance imaging (MRI) reconstruction lies in exploring inter-frame or inter-contrast information. Currently, the unrolled model, an…
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
Meng Ye, Mikael Kanski, Dong Yang +5
Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard for regional myocardium deformation and cardiac strain estimation. However, this technique has not been wide…
Deep Animation Video Interpolation in the Wild
Li Siyao, Shiyu Zhao, Weijiang Yu +4
In the animation industry, cartoon videos are usually produced at low frame rate since hand drawing of such frames is costly and time-consuming. Therefore, it is desirable to devel…
SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching
Xiangde Luo, Tao Song, Guotai Wang +5
Lung nodule detection from 3D Computed Tomography scans plays a vital role in efficient lung cancer screening. Despite the SOTA performance obtained by recent anchor-based detector…
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
Yunhe Gao, Zhiqiang Tang, Mu Zhou +1
Data augmentation has proved extremely useful by increasing training data variance to alleviate overfitting and improve deep neural networks' generalization performance. In medical…
Liver Fibrosis and NAS scoring from CT images using self-supervised learning and texture encoding
Ananya Jana, Hui Qu, Carlos D. Minacapelli +3
Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver diseases (CLD) which can progress to liver cancer. The severity and treatment of NAFLD i…
Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach
Yikai Zhang, Hui Qu, Qi Chang +3
Recently, Generative Adversarial Networks (GANs) have demonstrated their potential in federated learning, i.e., learning a centralized model from data privately hosted by multiple…
Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization
Long Zhao, Yuxiao Wang, Jiaping Zhao +7
We introduce a novel representation learning method to disentangle pose-dependent as well as view-dependent factors from 2D human poses. The method trains a network using cross-vie…
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Long Zhao, Ting Liu, Xi Peng +1
Adversarial data augmentation has shown promise for training robust deep neural networks against unforeseen data shifts or corruptions. However, it is difficult to define heuristic…
Cartoonish sketch-based face editing in videos using identity deformation transfer
Long Zhao, Fangda Han, Xi Peng +4
We address the problem of using hand-drawn sketches to create exaggerated deformations to faces in videos, such as enlarging the shape or modifying the position of eyes or mouth. T…