16 citations · 17 across the 3 of their papers we have counts for
6 papers · 1 filter
Pressure Eye: In-bed Contact Pressure Estimation via Contact-less Imaging
Shuangjun Liu, Sarah Ostadabbas
Computer vision has achieved great success in interpreting semantic meanings from images, yet estimating underlying (non-visual) physical properties of an object is often limited t…
Invariant Representation Learning for Infant Pose Estimation with Small Data
Xiaofei Huang, Nihang Fu, Shuangjun Liu +1
Infant motion analysis is a topic with critical importance in early childhood development studies. However, while the applications of human pose estimation have become more and mor…
Simultaneously-Collected Multimodal Lying Pose Dataset: Towards In-Bed Human Pose Monitoring under Adverse Vision Conditions
Shuangjun Liu, Xiaofei Huang, Nihang Fu +3
Computer vision (CV) has achieved great success in interpreting semantic meanings from images, yet CV algorithms can be brittle for tasks with adverse vision conditions and the one…
Seeing Under the Cover: A Physics Guided Learning Approach for In-Bed Pose Estimation
Shuangjun Liu, Sarah Ostadabbas
Human in-bed pose estimation has huge practical values in medical and healthcare applications yet still mainly relies on expensive pressure mapping (PM) solutions. In this paper, w…
A Semi-Supervised Data Augmentation Approach using 3D Graphical Engines
Shuangjun Liu, Sarah Ostadabbas
Deep learning approaches have been rapidly adopted across a wide range of fields because of their accuracy and flexibility, but require large labeled training datasets. This presen…
Inner Space Preserving Generative Pose Machine
Shuangjun Liu, Sarah Ostadabbas
Image-based generative methods, such as generative adversarial networks (GANs) have already been able to generate realistic images with much context control, specially when they ar…