3D Human Pose Estimation
309 papers with code • 25 benchmarks • 47 datasets
3D Human Pose Estimation is a computer vision task that involves estimating the 3D positions and orientations of body joints and bones from 2D images or videos. The goal is to reconstruct the 3D pose of a person in real-time, which can be used in a variety of applications, such as virtual reality, human-computer interaction, and motion analysis.
Benchmarks
These leaderboards are used to track progress in 3D Human Pose Estimation
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Libraries
Use these libraries to find 3D Human Pose Estimation models and implementationsDatasets
Human3.6M
Waymo Open Dataset
3DPW
AMASS
MPI-INF-3DHP
DensePose
LSP
Panoptic
AGORA
TotalCapture
Subtasks
Latest papers
Hourglass Tokenizer for Efficient Transformer-Based 3D Human Pose Estimation
Transformers have been successfully applied in the field of video-based 3D human pose estimation.
LiDAR-HMR: 3D Human Mesh Recovery from LiDAR
In recent years, point cloud perception tasks have been garnering increasing attention.
Efficient Domain Adaptation via Generative Prior for 3D Infant Pose Estimation
We further apply a guided diffusion model to domain adapt 3D adult pose to infant pose to supplement small datasets.
MotionAGFormer: Enhancing 3D Human Pose Estimation with a Transformer-GCNFormer Network
Our proposed GCNFormer module exploits the local relationship between adjacent joints, outputting a new representation that is complementary to the transformer output.
SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
caizhongang/SMPLer-X
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NeurIPS 2023
1) For the data scaling, we perform a systematic investigation on 32 EHPS datasets, including a wide range of scenarios that a model trained on any single dataset cannot handle.
FreeMan: Towards Benchmarking 3D Human Pose Estimation under Real-World Conditions
To facilitate the development of 3D pose estimation, we present FreeMan, the first large-scale, multi-view dataset collected under the real-world conditions.
Probabilistic Triangulation for Uncalibrated Multi-View 3D Human Pose Estimation
bymaths/probabilistic_triangulation
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ICCV 2023
The key idea is to use a probability distribution to model the camera pose and iteratively update the distribution from 2D features instead of using camera pose.
Refined Temporal Pyramidal Compression-and-Amplification Transformer for 3D Human Pose Estimation
hbing-l/rtpca
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Accurately estimating the 3D pose of humans in video sequences requires both accuracy and a well-structured architecture.
Fusing Monocular Images and Sparse IMU Signals for Real-time Human Motion Capture
We believe that the combination is complementary and able to solve the inherent difficulties of using one modality input, including occlusions, extreme lighting/texture, and out-of-view for visual mocap and global drifts for inertial mocap.
Spatio-temporal MLP-graph network for 3D human pose estimation
nies14/spatio-temporal-mlp-graph
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Graph convolutional networks and their variants have shown significant promise in 3D human pose estimation.
