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
TransPose: Keypoint Localization via TransformerCode1
Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular VideosCode1
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
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight TransferCode1
Temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded PeopleCode1
Monocular, One-stage, Regression of Multiple 3D PeopleCode2
Multi-Person Full Body Pose Estimation0
AID: Pushing the Performance Boundary of Human Pose Estimation with Information Dropping AugmentationCode1
Alleviating Human-level Shift : A Robust Domain Adaptation Method for Multi-person Pose EstimationCode0
Temporal Keypoint Matching and Refinement Network for Pose Estimation and Tracking0
Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation0
EfficientHRNet: Efficient Scaling for Lightweight High-Resolution Multi-Person Pose EstimationCode1
Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint EstimatesCode1
SMPR: Single-Stage Multi-Person Pose RegressionCode0
Self-supervised Keypoint Correspondences for Multi-Person Pose Estimation and Tracking in Videos0
Multi-Person Pose Estimation with Enhanced Feature Aggregation and Selection0
Learning Delicate Local Representations for Multi-Person Pose EstimationCode1
Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose EstimationCode1
AnimePose: Multi-person 3D pose estimation and animation0
Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation0
Multi-Level Network for High-Speed Multi-Person Pose Estimation0
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose EstimationCode1
DirectPose: Direct End-to-End Multi-Person Pose EstimationCode1
Single-shot 3D multi-person pose estimation in complex images0
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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