5 papers
Frame forecasting in cine MRI using the PCA respiratory motion model: comparing recurrent neural networks trained online and transformers
Michel Pohl, Mitsuru Uesaka, Hiroyuki Takahashi +2
Respiratory motion complicates accurate irradiation of thoraco-abdominal tumors during radiotherapy, as treatment-system latency entails target-location uncertainties. This work ad…
Quater-GCN: Enhancing 3D Human Pose Estimation with Orientation and Semi-supervised Training
Xingyu Song, Zhan Li, Shi Chen +1
3D human pose estimation is a vital task in computer vision, involving the prediction of human joint positions from images or videos to reconstruct a skeleton of a human in three-d…
An Animation-based Augmentation Approach for Action Recognition from Discontinuous Video
Xingyu Song, Zhan Li, Shi Chen +2
Action recognition, an essential component of computer vision, plays a pivotal role in multiple applications. Despite significant improvements brought by Convolutional Neural Netwo…
Real-time respiratory motion forecasting with online learning of recurrent neural networks for accurate targeting in externally guided radiotherapy
Michel Pohl, Mitsuru Uesaka, Hiroyuki Takahashi +2
In lung radiotherapy, infrared cameras can track reflective objects on the chest to estimate tumor motion due to breathing, but treatment system latencies hinder radiation beam pre…
GTAutoAct: An Automatic Datasets Generation Framework Based on Game Engine Redevelopment for Action Recognition
Xingyu Song, Zhan Li, Shi Chen +1
Current datasets for action recognition tasks face limitations stemming from traditional collection and generation methods, including the constrained range of action classes, absen…