SOTAVerified

Multi-Person Pose Estimation

Multi-person pose estimation is the task of estimating the pose of multiple people in one frame.

( Image credit: Human Pose Estimation with TensorFlow )

Papers

Showing 76100 of 151 papers

TitleStatusHype
Texture-Based Input Feature Selection for Action Recognition0
MDPose: Real-Time Multi-Person Pose Estimation via Mixture Density Model0
Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History0
Weakly Supervised 3D Multi-person Pose Estimation for Large-scale Scenes based on Monocular Camera and Single LiDAR0
JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Tracking0
QuickPose: Real-time Multi-view Multi-person Pose Estimation in Crowded Scenes0
Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation0
Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimation0
Bottom-up approaches for multi-person pose estimation and it's applications: A brief review0
BAPose: Bottom-Up Pose Estimation with Disentangled Waterfall RepresentationsCode0
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware AssociationCode0
Self-Supervision and Spatial-Sequential Attention Based Loss for Multi-Person Pose Estimation0
Shape-aware Multi-Person Pose Estimation from Multi-View Images0
A Benchmark for Gait Recognition under Occlusion Collected by Multi-Kinect SDAS0
Intelligent Carpet: Inferring 3D Human Pose From Tactile Signals0
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking0
Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices0
FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware ConvolutionsCode0
Learning Spatial Context with Graph Neural Network for Multi-Person Pose GroupingCode0
SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation0
A Global to Local Double Embedding Method for Multi-person Pose Estimation0
Efficient Human Pose Estimation with Depthwise Separable Convolution and Person Centroid Guided Joint Grouping0
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition0
Multi-Person Full Body Pose Estimation0
Alleviating Human-level Shift : A Robust Domain Adaptation Method for Multi-person Pose EstimationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RTMO-lmAP @0.5:0.9583.8Unverified
2BUCTD-W48 (w/cond. input from PETR, and generative sampling)mAP @0.5:0.9578.5Unverified
3I²R-Net (1st stage: HRFormer-B)mAP @0.5:0.9577.4Unverified
4ED-Pose (Swin-L)mAP @0.5:0.9576.6Unverified
5DETRPose-XmAP @0.5:0.9575.1Unverified
6DETRPose-LmAP @0.5:0.9573.3Unverified
7HRFormer-BmAP @0.5:0.9572.4Unverified
8BAPose (W32)mAP @0.5:0.9572.2Unverified
9DETRPose-MmAP @0.5:0.9572Unverified
10TransPose-HmAP @0.5:0.9571.8Unverified
#ModelMetricClaimedVerifiedStatus
1EvoPose2D-LTest AP76.8Unverified
2PoseFixTest AP76.7Unverified
3LitePose-STest AP56.7Unverified
4RSNAP0.79Unverified
5DarkPoseAP0.77Unverified
6UniPoseAP0.77Unverified
7CPN+AP0.73Unverified
8BAPoseAP0.73Unverified
9CenterGroupAP0.71Unverified
10OpenPifPafAP0.71Unverified
#ModelMetricClaimedVerifiedStatus
1SCIO (HRNet-48)AP79.2Unverified
2HRNet-W48plusAP78.7Unverified
3HRNet-W32AP76.2Unverified
4ResNet50AP73.7Unverified
5HigherHRNet (ScaleNet_P4)AP71.6Unverified
6HigherHRNet (HR-Net-48)AP70.5Unverified
7SMPR (HR-Net-32)AP70.2Unverified
8PersonLabAP68.7Unverified
9Identity Mapping HourglassAP68.1Unverified
10SPMAP66.9Unverified
#ModelMetricClaimedVerifiedStatus
1AlphaPoseAP82.1Unverified
2Generative Partition NetworksAP80.4Unverified
3SPMAP78.5Unverified
4RefineAP78Unverified
5Associative EmbeddingAP77.5Unverified
6Part Affinity FieldsAP75.6Unverified
7Articulated TrackingAP74.3Unverified
8Local Joint-to-Person AssociationAP62.2Unverified
9DeeperCutAP59.4Unverified
#ModelMetricClaimedVerifiedStatus
1MIPNet (gt-bb)AP5089.7Unverified
2I²R-Net (1st stage:TransPose-H)AP5085Unverified
3TransPose-HAP5082.7Unverified
4HRFormer-BAP5081.4Unverified
5SPMAP5067.5Unverified
6CrowdPoseAP5040.8Unverified
7SimplePoseAP5037.4Unverified
8Mask R-CNNAP5033.2Unverified
#ModelMetricClaimedVerifiedStatus
1HRNet-W48plusAP79.1Unverified
2HRNet-W32AP77.8Unverified
3ResNet50AP75.3Unverified
4InsPoseAP63.1Unverified
#ModelMetricClaimedVerifiedStatus
1PoseidonMean mAP87.8Unverified
2DCPoseMean mAP79Unverified
3PoseWarperMean mAP78Unverified
4RefineMean mAP73.8Unverified
#ModelMetricClaimedVerifiedStatus
1DCPoseMean mAP79.2Unverified
2PoseWarperMean mAP77.94Unverified
3PoseTrackMean mAP59.4Unverified
#ModelMetricClaimedVerifiedStatus
1DeeperCutAOP88.1Unverified
2DeepCutAOP86.5Unverified
3Generative Partition NetworksAP84.8Unverified
#ModelMetricClaimedVerifiedStatus
1CMU-PoseAP0.62Unverified
#ModelMetricClaimedVerifiedStatus
1PoseTrackMean mAP38.2Unverified
#ModelMetricClaimedVerifiedStatus
1PoseidonMean mAP88.3Unverified