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 551600 of 4228 papers

TitleStatusHype
Jointformer: Single-Frame Lifting Transformer with Error Prediction and Refinement for 3D Human Pose EstimationCode1
Globally Consistent Video Depth and Pose Estimation with Efficient Test-Time TrainingCode1
SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose EstimationCode1
RBP-Pose: Residual Bounding Box Projection for Category-Level Pose EstimationCode1
DETRs with Hybrid MatchingCode1
Live Stream Temporally Embedded 3D Human Body Pose and Shape EstimationCode1
3D Interacting Hand Pose Estimation by Hand De-occlusion and RemovalCode1
Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic ProjectionCode1
Approximate Differentiable Rendering with Algebraic SurfacesCode1
VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual DataCode1
OTPose: Occlusion-Aware Transformer for Pose Estimation in Sparsely-Labeled VideosCode1
BRACE: The Breakdancing Competition Dataset for Dance Motion SynthesisCode1
DH-AUG: DH Forward Kinematics Model Driven Augmentation for 3D Human Pose EstimationCode1
PoserNet: Refining Relative Camera Poses Exploiting Object DetectionsCode1
D^3FlowSLAM: Self-Supervised Dynamic SLAM with Flow Motion Decomposition and DINO GuidanceCode1
CATRE: Iterative Point Clouds Alignment for Category-level Object Pose RefinementCode1
TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled InstanceCode1
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in SpaceCode1
NeFSAC: Neurally Filtered Minimal SamplesCode1
Learning to Estimate External Forces of Human Motion in VideoCode1
CorrI2P: Deep Image-to-Point Cloud Registration via Dense CorrespondenceCode1
Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video SnippetCode1
HM3D-ABO: A Photo-realistic Dataset for Object-centric Multi-view 3D ReconstructionCode1
CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal PoseCode1
Certifiable 3D Object Pose Estimation: Foundations, Learning Models, and Self-TrainingCode1
I^2R-Net: Intra- and Inter-Human Relation Network for Multi-Person Pose EstimationCode1
Self-Supervised Learning of Image Scale and OrientationCode1
TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose EstimationCode1
GraphMLP: A Graph MLP-Like Architecture for 3D Human Pose EstimationCode1
APT-36K: A Large-scale Benchmark for Animal Pose Estimation and TrackingCode1
E2PN: Efficient SE(3)-Equivariant Point NetworkCode1
Efficient Human Pose Estimation via 3D Event Point CloudCode1
Mask2Hand: Learning to Predict the 3D Hand Pose and Shape from ShadowCode1
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collectionsCode1
SymFormer: End-to-end symbolic regression using transformer-based architectureCode1
VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-SynthesisCode1
Revealing the Dark Secrets of Masked Image ModelingCode1
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking KeypointsCode1
FvOR: Robust Joint Shape and Pose Optimization for Few-view Object ReconstructionCode1
Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality SelectionCode1
AggPose: Deep Aggregation Vision Transformer for Infant Pose EstimationCode1
BiCo-Net: Regress Globally, Match Locally for Robust 6D Pose EstimationCode1
Mobile-URSONet: an Embeddable Neural Network for Onboard Spacecraft Pose EstimationCode1
Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoCode1
A Simple Method to Boost Human Pose Estimation Accuracy by Correcting the Joint Regressor for the Human3.6m DatasetCode1
Coupled Iterative Refinement for 6D Multi-Object Pose EstimationCode1
Context-Aware Sequence Alignment using 4D Skeletal AugmentationCode1
PedRecNet: Multi-task deep neural network for full 3D human pose and orientation estimationCode1
Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose EstimationCode1
Self-Supervised Equivariant Learning for Oriented Keypoint DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1yoloposeAP5090.3Unverified
2ViTPose (ViTAE-G, ensemble)AP81.1Unverified
3ViTPose (ViTAE-G)AP80.9Unverified
4PoseBH-HAP79.5Unverified
5UDP-Pose-PSA(384x288)AP79.5Unverified
64xRSN-50 (ensemble)AP79.2Unverified
7UDP-Pose-PSA(256x192)AP78.9Unverified
8CCM+AP78.9Unverified
94xRSN-50AP78.6Unverified
10PCT (256x256)AP78.3Unverified
#ModelMetricClaimedVerifiedStatus
1PCT (swin-l, test set)PCKh-0.594.3Unverified
2Soft-gated Skip ConnectionsPCKh-0.594.1Unverified
3Cascade Feature AggregationPCKh-0.593.9Unverified
4PCT (swin-b, test set)PCKh-0.593.8Unverified
5TransPosePCKh-0.593.5Unverified
6UniHCP (FT)PCKh-0.593.2Unverified
74xRSN-50PCKh-0.593Unverified
8UniPosePCKh-0.592.7Unverified
9MSPNPCKh-0.592.6Unverified
10Spatial ContextPCKh-0.592.5Unverified
#ModelMetricClaimedVerifiedStatus
1ViTPose (ViTAE-G, GT bounding boxes)Test AP93.3Unverified
2UniHCP (direct eval)Test AP87.4Unverified
3PoseBH-HTest AP87Unverified
4RTMPose(RTMPose-l, GT bounding boxes)Test AP80.3Unverified
5TransPose-HValidation AP62.3Unverified
6BBox-Mask-Pose 2xTest AP48.3Unverified
7BUCTD (CID-W32)Test AP47.2Unverified
8HQNet (ViT-L)Test AP45.6Unverified
9MaskPose-bTest AP45Unverified
10CID (HRNet-W48)Test AP45Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPosePCK99.5Unverified
2Soft-gated Skip ConnectionsPCK94.8Unverified
3Residual Hourglass + ASR + AHOPCK94.5Unverified
4UniPosePCK94.5Unverified
5Chou et al. arXiv'17PCK94Unverified
6Pyramid Residual Modules (PRMs)PCK93.9Unverified
7Stacked hourglass + Inception-resnetPCK93.9Unverified
8Multi-Context AttentionPCK92.6Unverified
9FPDPCK90.8Unverified
10Part heatmap regression (ResNet-152)PCK90.7Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD-W48 (w/cond. input from PETR, and generative sampling)AP78.5Unverified
2ViTPose-GAP78.3Unverified
3BUCTD-W48 (w/cond. input from PETR)AP76.7Unverified
4SwinV2-L 1K-MIMAP75.5Unverified
5SwinV2-B 1K-MIMAP74.9Unverified
6BUCTD-W48AP72.9Unverified
7OpenPifPafAP70.5Unverified
8MIPNet (HRNet-W48)AP70Unverified
9KAPAO-LAP68.9Unverified
10KAPAO-MAP67.1Unverified
#ModelMetricClaimedVerifiedStatus
1CCNet (ViTPose-B_GT-bbox_256x192)AP78.1Unverified
2MogaNet-B (384x288)AP77.3Unverified
3ViTPose-B (Single-task_GT-bbox_256x192)AP77.3Unverified
4MogaNet-S (384x288)AP76.4Unverified
5Bias (HRNet_256x192)AP75.8Unverified
6ViTPose-B (Single-task_Det-bbox_256x192)AP75.8Unverified
7HRNet (256x192)AP75.3Unverified
8MogaNet-S (256x192)AP74.9Unverified
9MogaNet-T (256x192)AP73.2Unverified
10RLE (256x192)AP71.3Unverified
#ModelMetricClaimedVerifiedStatus
1Hulk(Finetune, ViT-L)AP37.1Unverified
2Hulk(Finetune, ViT-B)AP35.6Unverified
3HRFormer (HRFomer-B)AP34.4Unverified
4UniHCP (finetune)AP33.6Unverified
5HRNet (HRNet-w48 )AP33.5Unverified
6HRNet (HRNet-w32)AP32.3Unverified
7HRFormer (HRFomer-S)AP31.6Unverified
8SimpleBaseline (ResNet-152)AP29.9Unverified
9SimpleBaseline (ResNet-101)AP29.4Unverified
10SimpleBaseline (ResNet-50)AP28Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD (PETR, with generative sampling)APL83.7Unverified
2OmniPose (WASPv2)AP79.5Unverified
3MetaPrompt-SDAP79Unverified
4Hulk(Finetune, ViT-L)AP78.7Unverified
5BUCTD (PETR, with generative sampling)AP77.8Unverified
6Hulk(Finetune, ViT-B)AP77.5Unverified
7I²R-Net (1st stage:HRFormer-B)AP77.3Unverified
8PATH (Partial FT)AP77.1Unverified
9SOLIDER (swin-B)AP76.6Unverified
10PEFORMER-Xcit-dino-p8AP72.6Unverified
#ModelMetricClaimedVerifiedStatus
1GIM-DKMDUC1-Acc@0.25m,10°57.1Unverified
2GIM-LoFTRDUC1-Acc@0.25m,10°54.5Unverified
3GIM-SuperGlueDUC1-Acc@0.25m,10°53.5Unverified
4DKMDUC1-Acc@0.25m,10°51.5Unverified
5SuperGlueDUC1-Acc@0.25m,10°49Unverified
6LoFTRDUC1-Acc@0.25m,10°47.5Unverified
#ModelMetricClaimedVerifiedStatus
1AdaPoseMean mAP93.38Unverified
2DECA-D3Mean mAP88.75Unverified
3V2V-PoseNetMean mAP88.74Unverified
4A2JMean mAP88Unverified
5RENMean mAP84.9Unverified
6Multi-task learning + viewpoint invarianceMean mAP77.4Unverified
#ModelMetricClaimedVerifiedStatus
1SimpleBaseline + HANetMean PCK@0.299.6Unverified
2DeciWatchMean PCK@0.299Unverified
3LSTM PMMean PCK@0.293.6Unverified
4CPMMean PCK@0.291.9Unverified
5UniTrack_i18Mean PCK@0.280.5Unverified
#ModelMetricClaimedVerifiedStatus
14xRSN-50PCKh@0.593Unverified
2RefinePCKh@0.592.1Unverified
3EfficientPose IVPCKh@0.591.2Unverified
4OpenPosePCKh@0.588.8Unverified
5Adversarial LearningPCKh@0.588.6Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPoseMean PCK@0.299.4Unverified
2UniPose-LSTMMean PCK@0.299.3Unverified
3LSTM PMMean PCK@0.297.7Unverified
4Thin-SlicingMean PCK@0.296.5Unverified
5Iqbal et al.Mean PCK@0.281.1Unverified
#ModelMetricClaimedVerifiedStatus
1DP-RCNN-DeepLab (ResNet-101)AP68Unverified