activity
20162021
most citedDeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification

64 citations · 128 across the 12 of their papers we have counts for

collaborators

17 papers

cs.CV202119 cited

Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images

Jingru Yi, Pengxiang Wu, Hui Tang +7

Instance segmentation is of great importance for many biological applications, such as study of neural cell interactions, plant phenotyping, and quantitatively measuring how cells…

cs.CV20214 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

DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation

Liangjian Chen, Shih-Yao Lin, Yusheng Xie +3

Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formati…

cs.CV20207 cited

MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis

Zhenyu Wu, Duc Hoang, Shih-Yao Lin +5

Estimating the 3D hand pose from a monocular RGB image is important but challenging. A solution is training on large-scale RGB hand images with accurate 3D hand keypoint annotation…

eess.IV20203 cited

Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images

Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang +5

Scoliosis is a congenital disease that causes lateral curvature in the spine. Its assessment relies on the identification and localization of vertebrae in spinal X-ray images, conv…

cs.CV2020

Partly Supervised Multitask Learning

Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang +5

Semi-supervised learning has recently been attracting attention as an alternative to fully supervised models that require large pools of labeled data. Moreover, optimizing a model…