38 citations · 88 across the 14 of their papers we have counts for
8 papers · 1 filter
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
Jiewen Yang, Xinpeng Ding, Ziyang Zheng +2
Echocardiogram video segmentation plays an important role in cardiac disease diagnosis. This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentat…
GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation
Ziyang Zheng, Jiewen Yang, Xinpeng Ding +2
Cardiac structure segmentation from echocardiogram videos plays a crucial role in diagnosing heart disease. The combination of multi-view echocardiogram data is essential to enhanc…
How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images
Xinrong Hu, Xiaowei Xu, Yiyu Shi
The emerging scale segmentation model, Segment Anything (SAM), exhibits impressive capabilities in zero-shot segmentation for natural images. However, when applied to medical image…
ObjectAug: Object-level Data Augmentation for Semantic Image Segmentation
Jiawei Zhang, Yanchun Zhang, Xiaowei Xu
Semantic image segmentation aims to obtain object labels with precise boundaries, which usually suffers from overfitting. Recently, various data augmentation strategies like region…
C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer
Dongxu Wei, Xiaowei Xu, Haibin Shen +1
Human video motion transfer (HVMT) aims to synthesize videos that one person imitates other persons' actions. Although existing GAN-based HVMT methods have achieved great success,…
BUNET: Blind Medical Image Segmentation Based on Secure UNET
Song Bian, Xiaowei Xu, Weiwen Jiang +2
The strict security requirements placed on medical records by various privacy regulations become major obstacles in the age of big data. To ensure efficient machine learning as a s…
GAC-GAN: A General Method for Appearance-Controllable Human Video Motion Transfer
Dongxu Wei, Xiaowei Xu, Haibin Shen +1
Human video motion transfer has a wide range of applications in multimedia, computer vision and graphics. Recently, due to the rapid development of Generative Adversarial Networks…
PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence
Jinglan Liu, Jiaxin Zhang, Yukun Ding +3
This work explores the binarization of the deconvolution-based generator in a GAN for memory saving and speedup of image construction. Our study suggests that different from convol…