Pose Estimation

Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.

A common benchmark for this task is MPII Human Pose

( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1651–1675 of 4228 papers

Title	Date	Tasks	Status	Score
Heuristic Weakly Supervised 3D Human Pose Estimation	May 23, 2021	3D Human Pose Estimation3D Pose Estimation	CodeCode Available	5
Automatic vocal tract landmark localization from midsagittal MRI data	Jul 18, 2019	Face AlignmentPose Estimation	CodeCode Available	5
HEViTPose: High-Efficiency Vision Transformer for Human Pose Estimation	Nov 22, 2023	Pose Estimation	CodeCode Available	5
FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER	May 30, 2022	2D Human Pose Estimation3D Human Pose Estimation	CodeCode Available	5
Automatic Social Distance Estimation From Images: Performance Evaluation, Test Benchmark, and Algorithm	Mar 11, 2021	Human Detectionobject-detection	CodeCode Available	5
HDG-ODE: A Hierarchical Continuous-Time Model for Human Pose Forecasting	Jan 1, 2023	Human Pose ForecastingPose Estimation	CodeCode Available	5
HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose Estimation	May 7, 2025	3D Human Pose EstimationComputational Efficiency	CodeCode Available	5
Automatic Labeling of Parkinson’s Disease Gait Videos with Weak Supervision	Jun 25, 2023	3D Human Pose EstimationPose Estimation	CodeCode Available	5
HCA-Net: Hierarchical Context Attention Network for Intervertebral Disc Semantic Labeling	Nov 21, 2023	Pose Estimation	CodeCode Available	5
Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning	Mar 3, 2018	Deep LearningPose Estimation	CodeCode Available	5
Simple Multi-Resolution Representation Learning for Human Pose Estimation	Apr 14, 2020	Pose EstimationRepresentation Learning	CodeCode Available	5
Detect-and-Track: Efficient Pose Estimation in Videos	Dec 26, 2017	Human DetectionKeypoint Estimation	CodeCode Available	5
Detailed, accurate, human shape estimation from clothed 3D scan sequences	Mar 13, 2017	Pose EstimationVirtual Try-on	CodeCode Available	5
Head Pose Estimation Based on 5D Rotation Representation	Sep 3, 2024	Head Pose EstimationPose Estimation	CodeCode Available	5
Hierarchical Graph Networks for 3D Human Pose Estimation	Nov 23, 2021	3D Human Pose EstimationPose Estimation	CodeCode Available	5
HPERL: 3D Human Pose Estimation from RGB and LiDAR	Oct 16, 2020	3D Human Pose EstimationAction Recognition	CodeCode Available	5
Automatic Health Problem Detection from Gait Videos Using Deep Neural Networks	Jun 4, 2019	Feature EngineeringGeneral Classification	CodeCode Available	5
Single-Network Whole-Body Pose Estimation	Sep 30, 2019	Multi-Task LearningPose Estimation	CodeCode Available	5
Design Space Exploration on Efficient and Accurate Human Pose Estimation from Sparse IMU-Sensing	Jul 21, 2023	Pose Estimation	CodeCode Available	5
HandR2N2: Iterative 3D Hand Pose Estimation Using a Residual Recurrent Neural Network	Jan 1, 2023	3D Hand Pose EstimationHand Pose Estimation	CodeCode Available	5
Automatic detection of faults in race walking from a smartphone camera: a comparison of an Olympic medalist and university athletes	Aug 24, 2022	FairnessFault Detection	CodeCode Available	5
Hands Deep in Deep Learning for Hand Pose Estimation	Feb 24, 2015	Deep LearningHand Pose Estimation	CodeCode Available	5
Automatic Assessment of Infant Face and Upper-Body Symmetry as Early Signs of Torticollis	Oct 26, 2022	Pose Estimation	CodeCode Available	5
Automatic Analysis of Human Body Representations in Western Art	Oct 17, 2022	Pose Estimation	CodeCode Available	5
Addressing the challenges of loop detection in agricultural environments	Aug 28, 2024	Pose EstimationVisual Navigation	CodeCode Available	5

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All datasets COCO test-dev MPII Human Pose OCHuman Leeds Sports Poses CrowdPose COCO val2017 AIC COCO (Common Objects in Context)InLoc ITOP front-view J-HMDB MPII Single Person

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	yolopose	AP50	90.3	—	Unverified
2	ViTPose (ViTAE-G, ensemble)	AP	81.1	—	Unverified
3	ViTPose (ViTAE-G)	AP	80.9	—	Unverified
4	PoseBH-H	AP	79.5	—	Unverified
5	UDP-Pose-PSA(384x288)	AP	79.5	—	Unverified
6	4xRSN-50 (ensemble)	AP	79.2	—	Unverified
7	UDP-Pose-PSA(256x192)	AP	78.9	—	Unverified
8	CCM+	AP	78.9	—	Unverified
9	4xRSN-50	AP	78.6	—	Unverified
10	PCT (256x256)	AP	78.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PCT (swin-l, test set)	PCKh-0.5	94.3	—	Unverified
2	Soft-gated Skip Connections	PCKh-0.5	94.1	—	Unverified
3	Cascade Feature Aggregation	PCKh-0.5	93.9	—	Unverified
4	PCT (swin-b, test set)	PCKh-0.5	93.8	—	Unverified
5	TransPose	PCKh-0.5	93.5	—	Unverified
6	UniHCP (FT)	PCKh-0.5	93.2	—	Unverified
7	4xRSN-50	PCKh-0.5	93	—	Unverified
8	UniPose	PCKh-0.5	92.7	—	Unverified
9	MSPN	PCKh-0.5	92.6	—	Unverified
10	Spatial Context	PCKh-0.5	92.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ViTPose (ViTAE-G, GT bounding boxes)	Test AP	93.3	—	Unverified
2	UniHCP (direct eval)	Test AP	87.4	—	Unverified
3	PoseBH-H	Test AP	87	—	Unverified
4	RTMPose(RTMPose-l, GT bounding boxes)	Test AP	80.3	—	Unverified
5	TransPose-H	Validation AP	62.3	—	Unverified
6	BBox-Mask-Pose 2x	Test AP	48.3	—	Unverified
7	BUCTD (CID-W32)	Test AP	47.2	—	Unverified
8	HQNet (ViT-L)	Test AP	45.6	—	Unverified
9	MaskPose-b	Test AP	45	—	Unverified
10	CID (HRNet-W48)	Test AP	45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OmniPose	PCK	99.5	—	Unverified
2	Soft-gated Skip Connections	PCK	94.8	—	Unverified
3	Residual Hourglass + ASR + AHO	PCK	94.5	—	Unverified
4	UniPose	PCK	94.5	—	Unverified
5	Chou et al. arXiv'17	PCK	94	—	Unverified
6	Pyramid Residual Modules (PRMs)	PCK	93.9	—	Unverified
7	Stacked hourglass + Inception-resnet	PCK	93.9	—	Unverified
8	Multi-Context Attention	PCK	92.6	—	Unverified
9	FPD	PCK	90.8	—	Unverified
10	Part heatmap regression (ResNet-152)	PCK	90.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BUCTD-W48 (w/cond. input from PETR, and generative sampling)	AP	78.5	—	Unverified
2	ViTPose-G	AP	78.3	—	Unverified
3	BUCTD-W48 (w/cond. input from PETR)	AP	76.7	—	Unverified
4	SwinV2-L 1K-MIM	AP	75.5	—	Unverified
5	SwinV2-B 1K-MIM	AP	74.9	—	Unverified
6	BUCTD-W48	AP	72.9	—	Unverified
7	OpenPifPaf	AP	70.5	—	Unverified
8	MIPNet (HRNet-W48)	AP	70	—	Unverified
9	KAPAO-L	AP	68.9	—	Unverified
10	KAPAO-M	AP	67.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CCNet (ViTPose-B_GT-bbox_256x192)	AP	78.1	—	Unverified
2	MogaNet-B (384x288)	AP	77.3	—	Unverified
3	ViTPose-B (Single-task_GT-bbox_256x192)	AP	77.3	—	Unverified
4	MogaNet-S (384x288)	AP	76.4	—	Unverified
5	Bias (HRNet_256x192)	AP	75.8	—	Unverified
6	ViTPose-B (Single-task_Det-bbox_256x192)	AP	75.8	—	Unverified
7	HRNet (256x192)	AP	75.3	—	Unverified
8	MogaNet-S (256x192)	AP	74.9	—	Unverified
9	MogaNet-T (256x192)	AP	73.2	—	Unverified
10	RLE (256x192)	AP	71.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Hulk(Finetune, ViT-L)	AP	37.1	—	Unverified
2	Hulk(Finetune, ViT-B)	AP	35.6	—	Unverified
3	HRFormer (HRFomer-B)	AP	34.4	—	Unverified
4	UniHCP (finetune)	AP	33.6	—	Unverified
5	HRNet (HRNet-w48 )	AP	33.5	—	Unverified
6	HRNet (HRNet-w32)	AP	32.3	—	Unverified
7	HRFormer (HRFomer-S)	AP	31.6	—	Unverified
8	SimpleBaseline (ResNet-152)	AP	29.9	—	Unverified
9	SimpleBaseline (ResNet-101)	AP	29.4	—	Unverified
10	SimpleBaseline (ResNet-50)	AP	28	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BUCTD (PETR, with generative sampling)	APL	83.7	—	Unverified
2	OmniPose (WASPv2)	AP	79.5	—	Unverified
3	MetaPrompt-SD	AP	79	—	Unverified
4	Hulk(Finetune, ViT-L)	AP	78.7	—	Unverified
5	BUCTD (PETR, with generative sampling)	AP	77.8	—	Unverified
6	Hulk(Finetune, ViT-B)	AP	77.5	—	Unverified
7	I²R-Net (1st stage:HRFormer-B)	AP	77.3	—	Unverified
8	PATH (Partial FT)	AP	77.1	—	Unverified
9	SOLIDER (swin-B)	AP	76.6	—	Unverified
10	PEFORMER-Xcit-dino-p8	AP	72.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GIM-DKM	DUC1-Acc@0.25m,10°	57.1	—	Unverified
2	GIM-LoFTR	DUC1-Acc@0.25m,10°	54.5	—	Unverified
3	GIM-SuperGlue	DUC1-Acc@0.25m,10°	53.5	—	Unverified
4	DKM	DUC1-Acc@0.25m,10°	51.5	—	Unverified
5	SuperGlue	DUC1-Acc@0.25m,10°	49	—	Unverified
6	LoFTR	DUC1-Acc@0.25m,10°	47.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AdaPose	Mean mAP	93.38	—	Unverified
2	DECA-D3	Mean mAP	88.75	—	Unverified
3	V2V-PoseNet	Mean mAP	88.74	—	Unverified
4	A2J	Mean mAP	88	—	Unverified
5	REN	Mean mAP	84.9	—	Unverified
6	Multi-task learning + viewpoint invariance	Mean mAP	77.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SimpleBaseline + HANet	Mean PCK@0.2	99.6	—	Unverified
2	DeciWatch	Mean PCK@0.2	99	—	Unverified
3	LSTM PM	Mean PCK@0.2	93.6	—	Unverified
4	CPM	Mean PCK@0.2	91.9	—	Unverified
5	UniTrack_i18	Mean PCK@0.2	80.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	4xRSN-50	PCKh@0.5	93	—	Unverified
2	Refine	PCKh@0.5	92.1	—	Unverified
3	EfficientPose IV	PCKh@0.5	91.2	—	Unverified
4	OpenPose	PCKh@0.5	88.8	—	Unverified
5	Adversarial Learning	PCKh@0.5	88.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OmniPose	Mean PCK@0.2	99.4	—	Unverified
2	UniPose-LSTM	Mean PCK@0.2	99.3	—	Unverified
3	LSTM PM	Mean PCK@0.2	97.7	—	Unverified
4	Thin-Slicing	Mean PCK@0.2	96.5	—	Unverified
5	Iqbal et al.	Mean PCK@0.2	81.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DP-RCNN-DeepLab (ResNet-101)	AP	68	—	Unverified