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

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Showing 501–550 of 4228 papers

TitleStatusHype
ARTS: Semi-Analytical Regressor using Disentangled Skeletal Representations for Human Mesh Recovery from VideosCode1
Neural Active Structure-from-Motion in Dark and Textureless Environment—0
POSE: Pose estimation Of virtual Sync Exhibit systemCode0
Unlabeled Action Quality Assessment Based on Multi-dimensional Adaptive Constrained Dynamic Time Warping—0
Multi-modal Pose Diffuser: A Multimodal Generative Conditional Pose Prior—0
Object Pose Estimation Using Implicit Representation For Transparent Objects—0
Optimizing Multi-Task Learning for Accurate Spacecraft Pose Estimation—0
From Real Artifacts to Virtual Reference: A Robust Framework for Translating Endoscopic Images—0
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications—0
X-Fi: A Modality-Invariant Foundation Model for Multimodal Human Sensing—0
Occluded Human Pose Estimation based on Limb Joint Augmentation—0
Enhancing Single Image to 3D Generation using Gaussian Splatting and Hybrid Diffusion Priors—0
Towards Multi-Modal Animal Pose Estimation: A Survey and In-Depth AnalysisCode1
Look Gauss, No Pose: Novel View Synthesis using Gaussian Splatting without Accurate Pose InitializationCode2
LucidGrasp: Robotic Framework for Autonomous Manipulation of Laboratory Equipment with Different Degrees of Transparency via 6D Pose Estimation—0
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from VideosCode1
Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation—0
OmniPose6D: Towards Short-Term Object Pose Tracking in Dynamic Scenes from Monocular RGB—0
FürElise: Capturing and Physically Synthesizing Hand Motions of Piano Performance—0
Are Minimal Radial Distortion Solvers Necessary for Relative Pose Estimation?Code0
SpecTrack: Learned Multi-Rotation Tracking via Speckle ImagingCode0
Comparison of marker-less 2D image-based methods for infant pose estimation—0
Enhancing 3D Human Pose Estimation Amidst Severe Occlusion with Dual Transformer FusionCode0
LiteVLoc: Map-Lite Visual Localization for Image Goal NavigationCode2
Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on Predicted-View SynthesisCode0
A Generic Observer Design for Inertial Navigation Systems Using an LTV Framework—0
Unsupervised Prior Learning: Discovering Categorical Pose Priors from Videos—0
MonST3R: A Simple Approach for Estimating Geometry in the Presence of MotionCode5
HRVMamba: High-Resolution Visual State Space Model for Dense PredictionCode0
Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images—0
CLIP-Clique: Graph-based Correspondence Matching Augmented by Vision Language Models for Object-based Global Localization—0
Key-Grid: Unsupervised 3D Keypoints Detection using Grid Heatmap Features—0
Why Sample Space Matters: Keyframe Sampling Optimization for LiDAR-based Place RecognitionCode1
SGBA: Semantic Gaussian Mixture Model-Based LiDAR Bundle AdjustmentCode0
SurgeoNet: Realtime 3D Pose Estimation of Articulated Surgical Instruments from Stereo Images using a Synthetically-trained Network—0
GERA: Geometric Embedding for Efficient Point Registration Analysis—0
Pose Estimation of Buried Deep-Sea Objects using 3D Vision Deep Learning Models—0
RAD: A Dataset and Benchmark for Real-Life Anomaly Detection with Robotic ObservationsCode1
Classroom-Inspired Multi-Mentor Distillation with Adaptive Learning Strategies—0
SuperPose: Improved 6D Pose Estimation with Robust Tracking and Mask-Free Initialization—0
PuzzleBoard: A New Camera Calibration Pattern with Position EncodingCode1
Continual Human Pose Estimation for Incremental Integration of Keypoints and Pose Variations—0
PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and BeyondCode0
Exploiting Motion Prior for Accurate Pose Estimation of Dashboard Cameras—0
DynaWeightPnP: Toward global real-time 3D-2D solver in PnP without correspondences—0
Omni6D: Large-Vocabulary 3D Object Dataset for Category-Level 6D Object Pose EstimationCode1
Leveraging Anthropometric Measurements to Improve Human Mesh Estimation and Ensure Consistent Body ShapesCode1
AI-Powered Augmented Reality for Satellite Assembly, Integration and Test—0
FAFA: Frequency-Aware Flow-Aided Self-Supervision for Underwater Object Pose EstimationCode0
PseudoNeg-MAE: Self-Supervised Point Cloud Learning using Conditional Pseudo-Negative Embeddings—0
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All datasetsCOCO test-devMPII Human PoseOCHumanLeeds Sports PosesCrowdPoseCOCO val2017AICCOCO (Common Objects in Context)InLocITOP front-viewJ-HMDBMPII Single Person

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-DKMDUC1-Acc@0.25m,10°57.1—Unverified
2GIM-LoFTRDUC1-Acc@0.25m,10°54.5—Unverified
3GIM-SuperGlueDUC1-Acc@0.25m,10°53.5—Unverified
4DKMDUC1-Acc@0.25m,10°51.5—Unverified
5SuperGlueDUC1-Acc@0.25m,10°49—Unverified
6LoFTRDUC1-Acc@0.25m,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 PCK@0.299.6—Unverified
2DeciWatchMean PCK@0.299—Unverified
3LSTM PMMean PCK@0.293.6—Unverified
4CPMMean PCK@0.291.9—Unverified
5UniTrack_i18Mean PCK@0.280.5—Unverified
#ModelMetricClaimedVerifiedStatus
14xRSN-50PCKh@0.593—Unverified
2RefinePCKh@0.592.1—Unverified
3EfficientPose IVPCKh@0.591.2—Unverified
4OpenPosePCKh@0.588.8—Unverified
5Adversarial LearningPCKh@0.588.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPoseMean PCK@0.299.4—Unverified
2UniPose-LSTMMean PCK@0.299.3—Unverified
3LSTM PMMean PCK@0.297.7—Unverified
4Thin-SlicingMean PCK@0.296.5—Unverified
5Iqbal et al.Mean PCK@0.281.1—Unverified
#ModelMetricClaimedVerifiedStatus
1DP-RCNN-DeepLab (ResNet-101)AP68—Unverified