Multi-Hypotheses 3D Human Pose Estimation
12 papers with code • 3 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Multi-Hypotheses 3D Human Pose Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Human3.6M
MPI-INF-3DHP
AH36M
Most implemented papers
End-to-end Recovery of Human Shape and Pose
open-mmlab/mmpose
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CVPR 2018
The main objective is to minimize the reprojection loss of keypoints, which allow our model to be trained using images in-the-wild that only have ground truth 2D annotations.
Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network
chaneyddtt/Generating-Multiple-Hypotheses-for-3D-Human-Pose-Estimation-with-Mixture-Density-Network
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CVPR 2019
We argue that 3D human pose estimation from a monocular input is an inverse problem where multiple feasible solutions can exist.
Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking
ssfootball04/generative_pose
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ICCV 2019
Monocular 3D human-pose estimation from static images is a challenging problem, due to the curse of dimensionality and the ill-posed nature of lifting 2D-to-3D.
Weakly Supervised Generative Network for Multiple 3D Human Pose Hypotheses
chaneyddtt/weakly-supervised-3d-pose-generator
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In this paper, we propose a weakly supervised deep generative network to address the inverse problem and circumvent the need for ground truth 2D-to-3D correspondences.
Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows
twehrbein/Probabilistic-Monocular-3D-Human-Pose-Estimation-with-Normalizing-Flows
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ICCV 2021
3D human pose estimation from monocular images is a highly ill-posed problem due to depth ambiguities and occlusions.
Probabilistic Modeling for Human Mesh Recovery
This paper focuses on the problem of 3D human reconstruction from 2D evidence.
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild
akashsengupta1997/hierarchicalprobabilistic3dhuman
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ICCV 2021
Thus, it is desirable to estimate a distribution over 3D body shape and pose conditioned on the input image instead of a single 3D reconstruction.
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions
sinzlab/cgnf
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We evaluate cGNF on the Human~3. 6M dataset and show that cGNF provides a well-calibrated distribution estimate while being close to state-of-the-art in terms of overall minMPJPE.
GFPose: Learning 3D Human Pose Prior with Gradient Fields
Embracing/GFPose
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CVPR 2023
During the denoising process, GFPose implicitly incorporates pose priors in gradients and unifies various discriminative and generative tasks in an elegant framework.
MHEntropy: Entropy Meets Multiple Hypotheses for Pose and Shape Recovery
GloryyrolG/MHEntropy
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ICCV 2023
For monocular RGB-based 3D pose and shape estimation, multiple solutions are often feasible due to factors like occlusion and truncation.
