Pose Estimation On Ochuman

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Test AP

Validation AP

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

			Paper Title
ViTPose (ViTAE-G, GT bounding boxes)	93.3	92.8	ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation
UniHCP (direct eval)	87.4	-	UniHCP: A Unified Model for Human-Centric Perceptions
RTMPose(RTMPose-l, GT bounding boxes)	80.3	80.5	RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
BBox-Mask-Pose 2x	48.3	48.6	Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous Circle
BUCTD (CID-W32)	47.2	47.7	Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity
HQNet (ViT-L)	45.6	-	You Only Learn One Query: Learning Unified Human Query for Single-Stage Multi-Person Multi-Task Human-Centric Perception
CID (HRNet-W48)	45.0	46.1	Contextual Instance Decoupling for Robust Multi-Person Pose Estimation
MaskPose-b	45.0	45.3	Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous Circle
MIPNet (HRNet-W48)	42.5	42.0	Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation
HQNet (ResNet-50)	40.0	-	You Only Learn One Query: Learning Unified Human Query for Single-Stage Multi-Person Multi-Task Human-Centric Perception
HRNet-W48	37.2	37.8	Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation
HGG (AE+)	36.0	41.8	Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation
ResNet-152	33.3	41.0	Simple Baselines for Human Pose Estimation and Tracking
Associative Embedding+	32.8	40.0	Associative Embedding: End-to-End Learning for Joint Detection and Grouping
RMPE	30.7	38.8	RMPE: Regional Multi-person Pose Estimation
Associative Embedding	29.5	32.1	Associative Embedding: End-to-End Learning for Joint Detection and Grouping
ResNet-50	29.5	32.1	Simple Baselines for Human Pose Estimation and Tracking
TransPose-H	-	62.3	TransPose: Keypoint Localization via Transformer

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Pose Estimation On Ochuman | SOTA | HyperAI