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 20512100 of 4228 papers

TitleStatusHype
Leveraging Equivariant Features for Absolute Pose Regression0
Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Recovery0
Direct Dense Pose Estimation0
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image0
Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal RegressionCode1
DFNet: Enhance Absolute Pose Regression with Direct Feature MatchingCode1
A Unified Framework for Domain Adaptive Pose EstimationCode1
Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to OcclusionsCode1
Balanced MSE for Imbalanced Visual RegressionCode2
Spatial-Temporal Parallel Transformer for Arm-Hand Dynamic Estimation0
Temporal Feature Alignment and Mutual Information Maximization for Video-Based Human Pose EstimationCode1
OSOP: A Multi-Stage One Shot Object Pose Estimation Framework0
PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervisionCode2
Uncertainty-Aware Adaptation for Self-Supervised 3D Human Pose Estimation0
Efficient Virtual View Selection for 3D Hand Pose EstimationCode1
On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation0
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World0
OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object InteractionCode1
FS6D: Few-Shot 6D Pose Estimation of Novel ObjectsCode1
Optimizing Elimination Templates by Greedy Parameter SearchCode1
Uni6D: A Unified CNN Framework without Projection Breakdown for 6D Pose Estimation0
REGTR: End-to-end Point Cloud Correspondences with TransformersCode2
FD-SLAM: 3-D Reconstruction Using Features and Dense Matching0
A Visual Navigation Perspective for Category-Level Object Pose EstimationCode1
CrossFormer: Cross Spatio-Temporal Transformer for 3D Human Pose EstimationCode1
RayTran: 3D pose estimation and shape reconstruction of multiple objects from videos with ray-traced transformers0
RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose OptimizationCode1
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose EstimationCode3
AIMusicGuru: Music Assisted Human Pose Correction0
A Real World Dataset for Multi-view 3D Reconstruction0
Ray3D: ray-based 3D human pose estimation for monocular absolute 3D localizationCode1
DiffPoseNet: Direct Differentiable Camera Pose Estimation0
3D Human Pose Estimation Using Möbius Graph Convolutional Networks0
Occlusion-Aware Self-Supervised Monocular 6D Object Pose EstimationCode1
ViewFormer: NeRF-free Neural Rendering from Few Images Using TransformersCode2
Perspective Flow Aggregation for Data-Limited 6D Object Pose EstimationCode1
MatchFormer: Interleaving Attention in Transformers for Feature MatchingCode1
HybridCap: Inertia-aid Monocular Capture of Challenging Human Motions0
Transforming Gait: Video-Based Spatiotemporal Gait Analysis0
ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose EstimationCode1
On the sensitivity of pose estimation neural networks: rotation parameterizations, Lipschitz constants, and provable boundsCode0
DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose EstimationCode1
PosePipe: Open-Source Human Pose Estimation Pipeline for Clinical ResearchCode1
Pose-MUM : Reinforcing Key Points Relationship for Semi-Supervised Human Pose Estimation0
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise VotingCode1
P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose EstimationCode1
Distribution-Aware Single-Stage Models for Multi-Person 3D Pose EstimationCode1
SuperAnimal pretrained pose estimation models for behavioral analysisCode5
RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry0
6-DoF Pose Estimation of Household Objects for Robotic Manipulation: An Accessible Dataset and BenchmarkCode1
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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