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SOTA
Multi-Person Pose Estimation
Multi Person Pose Estimation On Coco
Multi Person Pose Estimation On Coco
Metrics
AP
Results
Performance results of various models on this benchmark
Columns
Model Name
AP
Paper Title
RSN
0.792
Learning Delicate Local Representations for Multi-Person Pose Estimation
DarkPose
0.774
Distribution-Aware Coordinate Representation for Human Pose Estimation
UniPose
0.768
X-Pose: Detecting Any Keypoints
CPN+
0.730
Cascaded Pyramid Network for Multi-Person Pose Estimation
BAPose
0.727
BAPose: Bottom-Up Pose Estimation with Disentangled Waterfall Representations
CenterGroup
0.714
The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation
OpenPifPaf
0.709
OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
Pose Residual Network
0.697
MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network
G-RMI*
0.685
Towards Accurate Multi-person Pose Estimation in the Wild
Supervising Self-Attention
0.665
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware Association
Associative Embedding
0.655
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
G-RMI
0.649
Towards Accurate Multi-person Pose Estimation in the Wild
PoseFix
-
PoseFix: Model-agnostic General Human Pose Refinement Network
LitePose-S
-
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation
EvoPose2D-L
-
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight Transfer
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Multi Person Pose Estimation On Coco | SOTA | HyperAI