Multi-Person Pose Estimation
81 papers with code • 11 benchmarks • 7 datasets
Multi-person pose estimation is the task of estimating the pose of multiple people in one frame.
( Image credit: Human Pose Estimation with TensorFlow )
Benchmarks
These leaderboards are used to track progress in Multi-Person Pose Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Multi-Person Pose Estimation models and implementations
MS COCO
MPII
PoseTrack
CrowdPose
OCHuman
COCO-WholeBody
PoPArt
Latest papers
Greedy Offset-Guided Keypoint Grouping for Human Pose Estimation
Given an image, we employ an Hourglass Network to infer all the keypoints from different persons indiscriminately as well as the guiding offsets connecting the adjacent keypoints belonging to the same persons.
HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
Differently, in whole-body pose estimation, the locations of fine-grained keypoints (68 on face, 21 on each hand and 3 on each foot) are estimated as well, which creates a scale variance problem that needs to be addressed.
FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions
aim-uofa/AdelaiDet
•
•
CVPR 2021
We propose a fully convolutional multi-person pose estimation framework using dynamic instance-aware convolutions, termed FCPose.
Learning Spatial Context with Graph Neural Network for Multi-Person Pose Grouping
More specifically, we design a Geometry-aware Association GNN that utilizes spatial information of the keypoints and learns local affinity from the global context.
Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
3dpose/3D-Multi-Person-Pose
•
•
CVPR 2021
Besides the integration of top-down and bottom-up networks, unlike existing pose discriminators that are designed solely for single person, and consequently cannot assess natural inter-person interactions, we propose a two-person pose discriminator that enforces natural two-person interactions.
Deep Dual Consecutive Network for Human Pose Estimation
Pose-Group/DCPose
•
•
CVPR 2021
Multi-frame human pose estimation in complicated situations is challenging.
Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing
tfzhou/MG-HumanParsing
•
•
CVPR 2021
To address the challenging task of instance-aware human part parsing, a new bottom-up regime is proposed to learn category-level human semantic segmentation as well as multi-person pose estimation in a joint and end-to-end manner.
OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e. g., a person's body joints) in multiple frames.
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation
rawalkhirodkar/MIPNet
•
•
ICCV 2021
Specifically, we achieve 70. 0 AP on CrowdPose and 42. 5 AP on OCHuman test sets, a significant improvement of 2. 4 AP and 6. 5 AP over the prior art, respectively.
Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views
In this work we propose an approach for estimating 3D human poses of multiple people from a set of calibrated cameras.
