61 citations · 102 across the 12 of their papers we have counts for
12 papers
Prior-Aware Synthetic Data to the Rescue: Animal Pose Estimation with Very Limited Real Data
Le Jiang, Shuangjun Liu, Xiangyu Bai +1
Accurately annotated image datasets are essential components for studying animal behaviors from their poses. Compared to the number of species we know and may exist, the existing l…
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…
Heuristic Weakly Supervised 3D Human Pose Estimation
Shuangjun Liu, Michael Wan, Sarah Ostadabbas
Monocular 3D human pose estimation from RGB images has attracted significant attention in recent years. However, recent models depend on supervised training with 3D pose ground tru…
Adapted Human Pose: Monocular 3D Human Pose Estimation with Zero Real 3D Pose Data
Shuangjun Liu, Naveen Sehgal, Sarah Ostadabbas
The ultimate goal for an inference model is to be robust and functional in real life applications. However, training vs. test data domain gaps often negatively affect model perform…
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…
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning Algorithms
Davoud Hejazi, Shuangjun Liu, Amirreza Farnoosh +2
Due to their inherent variabilities,nanomaterial-based sensors are challenging to translate into real-world applications,where reliability/reproducibility is key.Recently we showed…
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…
Bayesian Inference-enabled Precise Optical Wavelength Estimation using Transition Metal Dichalcogenide Thin Films
Davoud Hejazi, Shuangjun Liu, Sarah Ostadabbas +1
Despite its ability to draw precise inferences from large and complex datasets, the use of data analytics in the field of condensed matter and materials sciences -- where vast quan…
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…
In-Bed Pose Estimation: Deep Learning with Shallow Dataset
Shuangjun Liu, Yu Yin, Sarah Ostadabbas
Although human pose estimation for various computer vision (CV) applications has been studied extensively in the last few decades, yet in-bed pose estimation using camera-based vis…