Weakly-supervised 3D Human Pose Estimation
18 papers with code • 2 benchmarks • 2 datasets
This task targets at 3D Human Pose Estimation with fewer 3D annotation.
Benchmarks
These leaderboards are used to track progress in Weakly-supervised 3D Human Pose Estimation
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Libraries
Use these libraries to find Weakly-supervised 3D Human Pose Estimation models and implementations
Human3.6M
MPI-INF-3DHP
Latest papers
A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation
Furthermore, the pose estimator's optimization is not exposed to domain shifts, limiting its overall generalization ability.
Automatic Labeling of Parkinson’s Disease Gait Videos with Weak Supervision
mgholamikn/PD_Gait_labeling
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Medical Image Analysis 2023
The method obtained state-of-the-art results on the Human3. 6M dataset.
AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation
mgholamikn/AdaptPose
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CVPR 2022
To this end, we propose AdaptPose, an end-to-end framework that generates synthetic 3D human motions from a source dataset and uses them to fine-tune a 3D pose estimator.
Unsupervised 3D Pose Estimation for Hierarchical Dance Video Recognition
garfield-kh/posetriplet
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ICCV 2021
Dance experts often view dance as a hierarchy of information, spanning low-level (raw images, image sequences), mid-levels (human poses and bodypart movements), and high-level (dance genre).
Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry
vru2020/Pose_3D
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We present a self-supervised learning algorithm for 3D human pose estimation of a single person based on a multiple-view camera system and 2D body pose estimates for each view.
MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision
google-research/google-research
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CVPR 2022
In the era of deep learning, human pose estimation from multiple cameras with unknown calibration has received little attention to date.
Heuristic Weakly Supervised 3D Human Pose Estimation
However, recent models depend on supervised training with 3D pose ground truth data or known pose priors for their target domains.
PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation
jfzhang95/PoseAug
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CVPR 2021
To address this problem, we present PoseAug, a new auto-augmentation framework that learns to augment the available training poses towards a greater diversity and thus improve generalization of the trained 2D-to-3D pose estimator.
CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild
bastianwandt/CanonPose
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CVPR 2021
Human pose estimation from single images is a challenging problem in computer vision that requires large amounts of labeled training data to be solved accurately.
Cascaded deep monocular 3D human pose estimation with evolutionary training data
Nicholasli1995/EvoSkeleton
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CVPR 2020
End-to-end deep representation learning has achieved remarkable accuracy for monocular 3D human pose estimation, yet these models may fail for unseen poses with limited and fixed training data.
