SOTAVerified

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

Showing 951–1000 of 4228 papers

TitleStatusHype
3DP3: 3D Scene Perception via Probabilistic ProgrammingCode1
Deep Dual Consecutive Network for Human Pose EstimationCode1
The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose EstimationCode1
The Hilti SLAM Challenge DatasetCode1
Active Transfer Learning for Efficient Video-Specific Human Pose EstimationCode1
ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan FramesCode1
TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic RegressionCode1
Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusionsCode1
Towards Accurate Active Camera LocalizationCode1
Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose EstimationCode1
Mask as Supervision: Leveraging Unified Mask Information for Unsupervised 3D Pose EstimationCode1
Mask R-CNNCode1
Deep Global RegistrationCode1
Matching Is Not Enough: A Two-Stage Framework for Category-Agnostic Pose EstimationCode1
Toward fast and accurate human pose estimation via soft-gated skip connectionsCode1
Towards Accurate Cross-Domain In-Bed Human Pose EstimationCode1
AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the WildCode1
MEBOW: Monocular Estimation of Body Orientation In the WildCode1
NeRD: Neural 3D Reflection Symmetry DetectorCode1
MEEV: Body Mesh Estimation On Egocentric VideoCode1
NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose EstimationCode1
DeepIM: Deep Iterative Matching for 6D Pose EstimationCode1
Deep Implicit Statistical Shape Models for 3D Medical Image DelineationCode1
Neural Architecture Search for Joint Human Parsing and Pose EstimationCode1
Multi-View Video-Based 3D Hand Pose EstimationCode1
NeFSAC: Neurally Filtered Minimal SamplesCode1
Deep Keypoint-Based Camera Pose Estimation with Geometric ConstraintsCode1
Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose EstimationCode1
milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion SensingCode1
Deep Label Distribution Learning with Label AmbiguityCode1
Deep learning and machine learning techniques for head pose estimation: a surveyCode1
Towards Precise 3D Human Pose Estimation with Multi-Perspective Spatial-Temporal Relational TransformersCode1
MoCapDeform: Monocular 3D Human Motion Capture in Deformable ScenesCode1
Deep Learning-Based Human Pose Estimation: A SurveyCode1
Automatically Annotating Indoor Images with CAD Models via RGB-D ScansCode1
MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless SensingCode1
D^3FlowSLAM: Self-Supervised Dynamic SLAM with Flow Motion Decomposition and DINO GuidanceCode1
Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature FinetuningCode1
DeepURL: Deep Pose Estimation Framework for Underwater Relative LocalizationCode1
Mnemonic Descent Method: A recurrent process applied for end-to-end face alignmentCode1
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking KeypointsCode1
Modulated Graph Convolutional Network for 3D Human Pose EstimationCode1
MonoDiff9D: Monocular Category-Level 9D Object Pose Estimation via Diffusion ModelCode1
Multi-View Multi-Person 3D Pose Estimation with Plane Sweep StereoCode1
Monocular 3D Human Pose Estimation by Generation and Ordinal RankingCode1
Deep Soft Procrustes for Markerless Volumetric Sensor AlignmentCode1
Attention! A Lightweight 2D Hand Pose Estimation ApproachCode1
Monocular 3D Human Pose Estimation for Sports Broadcasts using Partial Sports Field RegistrationCode1
Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View GeometryCode1
Multi-Person Absolute 3D Human Pose Estimation with Weak Depth SupervisionCode1
Show:102550
← PrevPage 20 of 85Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1yoloposeAP5090.3—Unverified
2ViTPose (ViTAE-G, ensemble)AP81.1—Unverified
3ViTPose (ViTAE-G)AP80.9—Unverified
4PoseBH-HAP79.5—Unverified
5UDP-Pose-PSA(384x288)AP79.5—Unverified
64xRSN-50 (ensemble)AP79.2—Unverified
7UDP-Pose-PSA(256x192)AP78.9—Unverified
8CCM+AP78.9—Unverified
94xRSN-50AP78.6—Unverified
10PCT (256x256)AP78.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PCT (swin-l, test set)PCKh-0.594.3—Unverified
2Soft-gated Skip ConnectionsPCKh-0.594.1—Unverified
3Cascade Feature AggregationPCKh-0.593.9—Unverified
4PCT (swin-b, test set)PCKh-0.593.8—Unverified
5TransPosePCKh-0.593.5—Unverified
6UniHCP (FT)PCKh-0.593.2—Unverified
74xRSN-50PCKh-0.593—Unverified
8UniPosePCKh-0.592.7—Unverified
9MSPNPCKh-0.592.6—Unverified
10Spatial ContextPCKh-0.592.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTPose (ViTAE-G, GT bounding boxes)Test AP93.3—Unverified
2UniHCP (direct eval)Test AP87.4—Unverified
3PoseBH-HTest AP87—Unverified
4RTMPose(RTMPose-l, GT bounding boxes)Test AP80.3—Unverified
5TransPose-HValidation AP62.3—Unverified
6BBox-Mask-Pose 2xTest AP48.3—Unverified
7BUCTD (CID-W32)Test AP47.2—Unverified
8HQNet (ViT-L)Test AP45.6—Unverified
9MaskPose-bTest AP45—Unverified
10CID (HRNet-W48)Test AP45—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPosePCK99.5—Unverified
2Soft-gated Skip ConnectionsPCK94.8—Unverified
3Residual Hourglass + ASR + AHOPCK94.5—Unverified
4UniPosePCK94.5—Unverified
5Chou et al. arXiv'17PCK94—Unverified
6Pyramid Residual Modules (PRMs)PCK93.9—Unverified
7Stacked hourglass + Inception-resnetPCK93.9—Unverified
8Multi-Context AttentionPCK92.6—Unverified
9FPDPCK90.8—Unverified
10Part heatmap regression (ResNet-152)PCK90.7—Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD-W48 (w/cond. input from PETR, and generative sampling)AP78.5—Unverified
2ViTPose-GAP78.3—Unverified
3BUCTD-W48 (w/cond. input from PETR)AP76.7—Unverified
4SwinV2-L 1K-MIMAP75.5—Unverified
5SwinV2-B 1K-MIMAP74.9—Unverified
6BUCTD-W48AP72.9—Unverified
7OpenPifPafAP70.5—Unverified
8MIPNet (HRNet-W48)AP70—Unverified
9KAPAO-LAP68.9—Unverified
10KAPAO-MAP67.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CCNet (ViTPose-B_GT-bbox_256x192)AP78.1—Unverified
2MogaNet-B (384x288)AP77.3—Unverified
3ViTPose-B (Single-task_GT-bbox_256x192)AP77.3—Unverified
4MogaNet-S (384x288)AP76.4—Unverified
5Bias (HRNet_256x192)AP75.8—Unverified
6ViTPose-B (Single-task_Det-bbox_256x192)AP75.8—Unverified
7HRNet (256x192)AP75.3—Unverified
8MogaNet-S (256x192)AP74.9—Unverified
9MogaNet-T (256x192)AP73.2—Unverified
10RLE (256x192)AP71.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Hulk(Finetune, ViT-L)AP37.1—Unverified
2Hulk(Finetune, ViT-B)AP35.6—Unverified
3HRFormer (HRFomer-B)AP34.4—Unverified
4UniHCP (finetune)AP33.6—Unverified
5HRNet (HRNet-w48 )AP33.5—Unverified
6HRNet (HRNet-w32)AP32.3—Unverified
7HRFormer (HRFomer-S)AP31.6—Unverified
8SimpleBaseline (ResNet-152)AP29.9—Unverified
9SimpleBaseline (ResNet-101)AP29.4—Unverified
10SimpleBaseline (ResNet-50)AP28—Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD (PETR, with generative sampling)APL83.7—Unverified
2OmniPose (WASPv2)AP79.5—Unverified
3MetaPrompt-SDAP79—Unverified
4Hulk(Finetune, ViT-L)AP78.7—Unverified
5BUCTD (PETR, with generative sampling)AP77.8—Unverified
6Hulk(Finetune, ViT-B)AP77.5—Unverified
7I²R-Net (1st stage:HRFormer-B)AP77.3—Unverified
8PATH (Partial FT)AP77.1—Unverified
9SOLIDER (swin-B)AP76.6—Unverified
10PEFORMER-Xcit-dino-p8AP72.6—Unverified
#ModelMetricClaimedVerifiedStatus
1GIM-DKM[email protected],10°57.1—Unverified
2GIM-LoFTR[email protected],10°54.5—Unverified
3GIM-SuperGlue[email protected],10°53.5—Unverified
4DKM[email protected],10°51.5—Unverified
5SuperGlue[email protected],10°49—Unverified
6LoFTR[email protected],10°47.5—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaPoseMean mAP93.38—Unverified
2DECA-D3Mean mAP88.75—Unverified
3V2V-PoseNetMean mAP88.74—Unverified
4A2JMean mAP88—Unverified
5RENMean mAP84.9—Unverified
6Multi-task learning + viewpoint invarianceMean mAP77.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SimpleBaseline + HANetMean [email protected]99.6—Unverified
2DeciWatchMean [email protected]99—Unverified
3LSTM PMMean [email protected]93.6—Unverified
4CPMMean [email protected]91.9—Unverified
5UniTrack_i18Mean [email protected]80.5—Unverified
#ModelMetricClaimedVerifiedStatus
14xRSN-50[email protected]93—Unverified
2Refine[email protected]92.1—Unverified
3EfficientPose IV[email protected]91.2—Unverified
4OpenPose[email protected]88.8—Unverified
5Adversarial Learning[email protected]88.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPoseMean [email protected]99.4—Unverified
2UniPose-LSTMMean [email protected]99.3—Unverified
3LSTM PMMean [email protected]97.7—Unverified
4Thin-SlicingMean [email protected]96.5—Unverified
5Iqbal et al.Mean [email protected]81.1—Unverified
#ModelMetricClaimedVerifiedStatus
1DP-RCNN-DeepLab (ResNet-101)AP68—Unverified