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 401–450 of 4228 papers

TitleStatusHype
BLADE: Single-view Body Mesh Learning through Accurate Depth Estimation—0
LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation Models—0
MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 SecondsCode4
Attention-Enhanced Lightweight Hourglass Network for Human Pose EstimationCode0
Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential InformationCode1
CCS: Continuous Learning for Customized Incremental Wireless Sensing Services—0
ProPLIKS: Probablistic 3D human body pose estimation—0
DualPM: Dual Posed-Canonical Point Maps for 3D Shape and Pose Reconstruction—0
Targeted Hard Sample Synthesis Based on Estimated Pose and Occlusion Error for Improved Object Pose Estimation—0
An indoor DSO-based ceiling-vision odometry system for indoor industrial environments—0
Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis—0
NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images—0
A Bidirectional Siamese Recurrent Neural Network for Accurate Gait Recognition Using Body Landmarks—0
EgoCast: Forecasting Egocentric Human Pose in the Wild—0
ProbPose: A Probabilistic Approach to 2D Human Pose EstimationCode2
Cascaded Multi-Scale Attention for Enhanced Multi-Scale Feature Extraction and Interaction with Low-Resolution ImagesCode0
CLERF: Contrastive LEaRning for Full Range Head Pose Estimation—0
emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose EstimationCode3
CRISP: Object Pose and Shape Estimation with Test-Time Adaptation—0
SF-Loc: A Visual Mapping and Geo-Localization System based on Sparse Visual Structure FramesCode2
HandOS: 3D Hand Reconstruction in One Stage—0
MamKPD: A Simple Mamba Baseline for Real-Time 2D Keypoint Detection—0
Cross-Modal Visual Relocalization in Prior LiDAR Maps Utilizing Intensity Textures—0
6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting—0
Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous CircleCode3
Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion ModelsCode1
FlashSLAM: Accelerated RGB-D SLAM for Real-Time 3D Scene Reconstruction with Gaussian Splatting—0
ESCAPE: Equivariant Shape Completion via Anchor Point Encoding—0
Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature FinetuningCode1
Diorama: Unleashing Zero-shot Single-view 3D Scene Modeling—0
Waterfall Transformer for Multi-person Pose Estimation—0
HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videos—0
GMS-VINS:Multi-category Dynamic Objects Semantic Segmentation for Enhanced Visual-Inertial Odometry Using a Promptable Foundation Model—0
AC3D: Analyzing and Improving 3D Camera Control in Video Diffusion Transformers—0
XR-MBT: Multi-modal Full Body Tracking for XR through Self-Supervision with Learned Depth Point Cloud Registration—0
Boost 3D Reconstruction using Diffusion-based Monocular Camera CalibrationCode2
RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation through Embedding Predictive Pre-TrainingCode1
GMFlow: Global Motion-Guided Recurrent Flow for 6D Object Pose Estimation—0
SelfSplat: Pose-Free and 3D Prior-Free Generalizable 3D Gaussian Splatting—0
Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Generative Latent Priors—0
Geometric Point Attention Transformer for 3D Shape Reassembly—0
Edge Weight Prediction For Category-Agnostic Pose EstimationCode1
Diffusion Features for Zero-Shot 6DoF Object Pose EstimationCode0
SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting SynthesisCode2
UNOPose: Unseen Object Pose Estimation with an Unposed RGB-D Reference Image—0
One Diffusion to Generate Them AllCode4
Generalizable Single-view Object Pose Estimation by Two-side Generating and MatchingCode1
PEnG: Pose-Enhanced Geo-LocalisationCode0
Personalization of Wearable Sensor-Based Joint Kinematic Estimation Using Computer Vision for Hip Exoskeleton Applications—0
mmWave Radar for Sit-to-Stand Analysis: A Comparative Study with Wearables and Kinect—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