activity
20192021
most citedShifted Chunk Transformer for Spatio-Temporal Representational Learning

7 citations · 46 across the 11 of their papers we have counts for

collaborators

11 papers

cs.SD2021★ 2 cited

SpeechNAS: Towards Better Trade-off between Latency and Accuracy for Large-Scale Speaker Verification

Wentao Zhu, Tianlong Kong, Shun Lu +6

Recently, x-vector has been a successful and popular approach for speaker verification, which employs a time delay neural network (TDNN) and statistics pooling to extract speaker c…

cs.CV2021★ 7 cited

Shifted Chunk Transformer for Spatio-Temporal Representational Learning

Xuefan Zha, Wentao Zhu, Tingxun Lv +2

Spatio-temporal representational learning has been widely adopted in various fields such as action recognition, video object segmentation, and action anticipation. Previous spatio-…

eess.IV2021★ 1 cited

Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures

Holger R. Roth, Dong Yang, Wenqi Li +5

Building robust deep learning-based models requires diverse training data, ideally from several sources. However, these datasets cannot be combined easily because of patient privac…

cs.CV2021★ 4 cited

Test-Time Training for Deformable Multi-Scale Image Registration

Wentao Zhu, Yufang Huang, Daguang Xu +3

Registration is a fundamental task in medical robotics and is often a crucial step for many downstream tasks such as motion analysis, intra-operative tracking and image segmentatio…

cs.CV2020★ 3 cited

Deformable Gabor Feature Networks for Biomedical Image Classification

Xuan Gong, Xin Xia, Wentao Zhu +3

In recent years, deep learning has dominated progress in the field of medical image analysis. We find however, that the ability of current deep learning approaches to represent the…

cs.CV2020★ 7 cited

Cycle-Consistent Adversarial Autoencoders for Unsupervised Text Style Transfer

Yufang Huang, Wentao Zhu, Deyi Xiong +3

Unsupervised text style transfer is full of challenges due to the lack of parallel data and difficulties in content preservation. In this paper, we propose a novel neural approach…

cs.CV2020★ 5 cited

Multi-Domain Image Completion for Random Missing Input Data

Liyue Shen, Wentao Zhu, Xiaosong Wang +9

Multi-domain data are widely leveraged in vision applications taking advantage of complementary information from different modalities, e.g., brain tumor segmentation from multi-par…

cs.CV2020★ 6 cited

LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation

Wentao Zhu, Can Zhao, Wenqi Li +3

Deep Learning (DL) models are becoming larger, because the increase in model size might offer significant accuracy gain. To enable the training of large deep networks, data paralle…

cs.CV2020★ 7 cited

TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting

Zhuoqian Yang, Wentao Zhu, Wayne Wu +4

We present a lightweight video motion retargeting approach TransMoMo that is capable of transferring motion of a person in a source video realistically to another video of a target…

cs.CV2019★ 4 cited

NeurReg: Neural Registration and Its Application to Image Segmentation

Wentao Zhu, Andriy Myronenko, Ziyue Xu +5

Registration is a fundamental task in medical image analysis which can be applied to several tasks including image segmentation, intra-operative tracking, multi-modal image alignme…

eess.IV2019

Cardiac Segmentation of LGE MRI with Noisy Labels

Holger Roth, Wentao Zhu, Dong Yang +2

In this work, we attempt the segmentation of cardiac structures in late gadolinium-enhanced (LGE) magnetic resonance images (MRI) using only minimal supervision in a two-step appro…