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 51–100 of 4228 papers

TitleStatusHype
ArrowPose: Segmentation, Detection, and 5 DoF Pose Estimation Network for Colorless Point Clouds—0
Hierarchical Scoring with 3D Gaussian Splatting for Instance Image-Goal Navigation—0
UA-Pose: Uncertainty-Aware 6D Object Pose Estimation and Online Object Completion with Partial References—0
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models—0
Deep Inertial Pose: A deep learning approach for human pose estimation—0
You Only Estimate Once: Unified, One-stage, Real-Time Category-level Articulated Object 6D Pose Estimation for Robotic Grasping—0
Dy3DGS-SLAM: Monocular 3D Gaussian Splatting SLAM for Dynamic Environments—0
SurGSplat: Progressive Geometry-Constrained Gaussian Splatting for Surgical Scene Reconstruction—0
On-the-fly Reconstruction for Large-Scale Novel View Synthesis from Unposed Images—0
LGM-Pose: A Lightweight Global Modeling Network for Real-time Human Pose Estimation—0
CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx—0
SupeRANSAC: One RANSAC to Rule Them AllCode3
Rectified Point Flow: Generic Point Cloud Pose Estimation—0
Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation—0
cuVSLAM: CUDA accelerated visual odometry and mapping—0
Learning Pyramid-structured Long-range Dependencies for 3D Human Pose EstimationCode0
GeneA-SLAM2: Dynamic SLAM with AutoEncoder-Preprocessed Genetic Keypoints Resampling and Depth Variance-Guided Dynamic Region RemovalCode1
PCIE_Pose Solution for EgoExo4D Pose and Proficiency Estimation Challenge—0
Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data—0
6D Pose Estimation on Point Cloud Data through Prior Knowledge Integration: A Case Study in Autonomous Disassembly—0
Event-based Egocentric Human Pose Estimation in Dynamic Environment—0
4DTAM: Non-Rigid Tracking and Mapping via Dynamic Surface Gaussians—0
MultiFormer: A Multi-Person Pose Estimation System Based on CSI and Attention Mechanism—0
ReassembleNet: Learnable Keypoints and Diffusion for 2D Fresco Reconstruction—0
Why Not Replace? Sustaining Long-Term Visual Localization via Handcrafted-Learned Feature Collaboration on CPUCode1
Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery—0
Pose Splatter: A 3D Gaussian Splatting Model for Quantifying Animal Pose and Appearance—0
PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose EstimationCode1
Towards Texture- And Shape-Independent 3D Keypoint Estimation in Birds—0
GMatch: Geometry-Constrained Feature Matching for RGB-D Object Pose Estimation—0
Object-Focus Actor for Data-efficient Robot Generalization Dexterous Manipulation—0
UPTor: Unified 3D Human Pose Dynamics and Trajectory Prediction for Human-Robot Interaction—0
The Way Up: A Dataset for Hold Usage Detection in Sport Climbing—0
KinTwin: Imitation Learning with Torque and Muscle Driven Biomechanical Models Enables Precise Replication of Able-Bodied and Impaired Movement from Markerless Motion Capture—0
Recollection from Pensieve: Novel View Synthesis via Learning from Uncalibrated VideosCode2
ElderFallGuard: Real-Time IoT and Computer Vision-Based Fall Detection System for Elderly Safety—0
Black-box Adversaries from Latent Space: Unnoticeable Attacks on Human Pose and Shape Estimation—0
Keypoints as Dynamic Centroids for Unified Human Pose and Segmentation—0
SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision—0
MTevent: A Multi-Task Event Camera Dataset for 6D Pose Estimation and Moving Object DetectionCode0
PoseBench3D: A Cross-Dataset Analysis Framework for 3D Human Pose EstimationCode1
RefPose: Leveraging Reference Geometric Correspondences for Accurate 6D Pose Estimation of Unseen Objects—0
APR-Transformer: Initial Pose Estimation for Localization in Complex Environments through Absolute Pose RegressionCode0
UMotion: Uncertainty-driven Human Motion Estimation from Inertial and Ultra-wideband UnitsCode1
Sleep Position Classification using Transfer Learning for Bed-based Pressure Sensors—0
When Dance Video Archives Challenge Computer Vision—0
Enabling Privacy-Aware AI-Based Ergonomic Analysis—0
CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground EnvironmentsCode3
Active Perception for Tactile Sensing: A Task-Agnostic Attention-Based Approach—0
An Efficient Method for Accurate Pose Estimation and Error Correction of Cuboidal Objects—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