BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets
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Abstract (arXiv)
Human motion analysis has seen drastic improvements recently, however, due to the lack of representative datasets, for clinical in-bed scenarios it is still lagging behind. To address this issue, we implemented BlanketGen, a pipeline that augments videos with synthetic blanket occlusions. With this pipeline, we generated an augmented version of the pose estimation dataset 3DPW called BlanketGen-3DPW. We then used this new dataset to fine-tune a Deep Learning model to improve its performance in these scenarios with promising results. Code and further information are available at https://gitlab.inesctec.pt/brain-lab/brain-lab-public/blanket-gen-releases.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 10 of its 24 references that are in the map. First posted on arXiv 21 Oct 2022.
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10 of 24 references.
References · 10
- 2014Microsoft COCO: Common Objects in Contextcited by 17,608
- 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,612
- 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 695
- 2016Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervisioncited by 494
- 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 307
- 2015DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimationcited by 117
- 2022DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimationcited by 29
- 2021Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptationcited by 24
- 2021BodyPressure -- Inferring Body Pose and Contact Pressure from a Depth Imagecited by 20
- 2020A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectivescited by 18
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