363 citations · 695 across the 14 of their papers we have counts for
5 papers · 1 filter
Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition
Yi-Fan Song, Zhang Zhang, Caifeng Shan +1
One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints. However, the complexity of the State-Of-The-Art (SOTA…
Weakly-supervised Learning For Catheter Segmentation in 3D Frustum Ultrasound
Hongxu Yang, Caifeng Shan, Alexander F. Kolen +1
Accurate and efficient catheter segmentation in 3D ultrasound (US) is essential for cardiac intervention. Currently, the state-of-the-art segmentation algorithms are based on convo…
Richly Activated Graph Convolutional Network for Robust Skeleton-based Action Recognition
Yi-Fan Song, Zhang Zhang, Caifeng Shan +1
Current methods for skeleton-based human action recognition usually work with complete skeletons. However, in real scenarios, it is inevitable to capture incomplete or noisy skelet…
CANet: Context Aware Network for 3D Brain Glioma Segmentation
Zhihua Liu, Lei Tong, Long Chen +7
Automated segmentation of brain glioma plays an active role in diagnosis decision, progression monitoring and surgery planning. Based on deep neural networks, previous studies have…
Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet
Hongxu Yang, Caifeng Shan, Alexander F. Kolen +1
Catheter segmentation in 3D ultrasound is important for computer-assisted cardiac intervention. However, a large amount of labeled images are required to train a successful deep co…