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
Latest papers
BAPose: Bottom-Up Pose Estimation with Disentangled Waterfall Representations
We propose BAPose, a novel bottom-up approach that achieves state-of-the-art results for multi-person pose estimation.
Robust Pose Estimation in Crowded Scenes with Direct Pose-Level Inference
kennethwdk/pinet
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NeurIPS 2021
Instead of inferring individual keypoints, the Pose-level Inference Network (PINet) directly infers the complete pose cues for a person from his/her visible body parts.
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware Association
This paper presents a new method to solve keypoint detection and instance association by using Transformer.
HRFormer: High-Resolution Transformer for Dense Prediction
HRNet/HRFormer
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We present a High-Resolution Transformer (HRFormer) that learns high-resolution representations for dense prediction tasks, in contrast to the original Vision Transformer that produces low-resolution representations and has high memory and computational cost.
The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation
dvl-tum/center-group
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ICCV 2021
We introduce CenterGroup, an attention-based framework to estimate human poses from a set of identity-agnostic keypoints and person center predictions in an image.
Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images
wusize/multiview_pose
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ICCV 2021
Following the top-down paradigm, we decompose the task into two stages, i. e. person localization and pose estimation.
Learning Local-Global Contextual Adaptation for Multi-Person Pose Estimation
cherubicXN/logocap
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CVPR 2022
This paper studies the problem of multi-person pose estimation in a bottom-up fashion.
Human Pose Regression with Residual Log-likelihood Estimation
open-mmlab/mmpose
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ICCV 2021
In light of this, we propose a novel regression paradigm with Residual Log-likelihood Estimation (RLE) to capture the underlying output distribution.
PoseDet: Fast Multi-Person Pose Estimation Using Pose Embedding
IIGROUP/PoseDet
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This simple framework achieves an unprecedented speed and a competitive accuracy on the COCO benchmark compared with state-of-the-art methods.
InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation
Multi-person pose estimation is an attractive and challenging task.
