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
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Libraries
Use these libraries to find Multi-Person Pose Estimation models and implementations
MS COCO
MPII
PoseTrack
CrowdPose
OCHuman
COCO-WholeBody
PoPArt
Most implemented papers
DirectPose: Direct End-to-End Multi-Person Pose Estimation
aim-uofa/adet
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We propose the first direct end-to-end multi-person pose estimation framework, termed DirectPose.
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
hellojialee/Improved-Body-Parts
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We rethink a well-know bottom-up approach for multi-person pose estimation and propose an improved one.
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision.
Distribution-Aware Coordinate Representation for Human Pose Estimation
leoxiaobin/deep-high-resolution-net.pytorch
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CVPR 2020
Interestingly, we found that the process of decoding the predicted heatmaps into the final joint coordinates in the original image space is surprisingly significant for human pose estimation performance, which nevertheless was not recognised before.
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.
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
open-mmlab/mmpose
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NeurIPS 2017
We introduce associative embedding, a novel method for supervising convolutional neural networks for the task of detection and grouping.
Cascaded Pyramid Network for Multi-Person Pose Estimation
chenyilun95/tf-cpn
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CVPR 2018
In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
This paper considers the task of articulated human pose estimation of multiple people in real world images.
MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network
salihkaragoz/pose-residual-network-pytorch
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ECCV 2018
In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.
Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
mks0601/3DMPPE_POSENET_RELEASE
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ICCV 2019
Although significant improvement has been achieved recently in 3D human pose estimation, most of the previous methods only treat a single-person case.
