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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 4228 papers

TitleStatusHype
iG-6DoF: Model-free 6DoF Pose Estimation for Unseen Object via Iterative 3D Gaussian Splatting—0
Pos3R: 6D Pose Estimation for Unseen Objects Made Easy—0
Rethinking Correspondence-based Category-Level Object Pose Estimation—0
M3GYM: A Large-Scale Multimodal Multi-view Multi-person Pose Dataset for Fitness Activity Understanding in Real-world Settings—0
PIDLoc: Cross-View Pose Optimization Network Inspired by PID ControllersCode1
BIGS: Bimanual Category-agnostic Interaction Reconstruction from Monocular Videos via 3D Gaussian Splatting—0
DynPose: Largely Improving the Efficiency of Human Pose Estimation by a Simple Dynamic FrameworkCode0
Hand-held Object Reconstruction from RGB Video with Dynamic Interaction—0
UniHOPE: A Unified Approach for Hand-Only and Hand-Object Pose EstimationCode0
Leveraging Global Stereo Consistency for Category-Level Shape and 6D Pose Estimation from Stereo Images—0
Unsupervised Discovery of Facial Landmarks and Head Pose—0
GraphI2P: Image-to-Point Cloud Registration with Exploring Pattern of Correspondence via Graph Learning—0
BLADE: Single-view Body Mesh Estimation through Accurate Depth Estimation—0
DiffLO: Semantic-Aware LiDAR Odometry with Diffusion-Based Refinement—0
Learning to Filter Outlier Edges in Global SfMCode1
Dynamic Camera Poses and Where to Find Them—0
MVDoppler-Pose: Multi-Modal Multi-View mmWave Sensing for Long-Distance Self-Occluded Human Walking Pose Estimation—0
MODA: Motion-Drift Augmentation for Inertial Human Motion Analysis—0
CroCoDL: Cross-device Collaborative Dataset for Localization—0
MV-SSM: Multi-View State Space Modeling for 3D Human Pose Estimation—0
SCFlow2: Plug-and-Play Object Pose Refiner with Shape-Constraint Scene Flow—0
A Novel Convolution and Attention Mechanism-based Model for 6D Object Pose Estimation—0
Relative Pose Observability Analysis Using Dual Quaternions—0
ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation LearningCode0
Frequency-aware Event Cloud Network—0
Towards nation-wide analytical healthcare infrastructures: A privacy-preserving augmented knee rehabilitation case studyCode0
KeyGS: A Keyframe-Centric Gaussian Splatting Method for Monocular Image Sequences—0
Exploiting Aggregation and Segregation of Representations for Domain Adaptive Human Pose EstimationCode0
MambaVO: Deep Visual Odometry Based on Sequential Matching Refinement and Training Smoothing—0
GSplatLoc: Ultra-Precise Camera Localization via 3D Gaussian SplattingCode2
Dust to Tower: Coarse-to-Fine Photo-Realistic Scene Reconstruction from Sparse Uncalibrated Images—0
Optimizing Local-Global Dependencies for Accurate 3D Human Pose EstimationCode0
Reconstructing People, Places, and CamerasCode2
Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual OdometryCode0
FACTS: Fine-Grained Action Classification for Tactical Sports—0
EasyVis2: A Real Time Multi-view 3D Visualization for Laparoscopic Surgery Training Enhanced by a Deep Neural Network YOLOv8-Pose—0
Can Generative Video Models Help Pose Estimation?—0
Monkey Transfer Learning Can Improve Human Pose Estimation—0
Scaling 4D Representations—0
Pre-training a Density-Aware Pose Transformer for Robust LiDAR-based 3D Human Pose EstimationCode1
Level-Set Parameters: Novel Representation for 3D Shape AnalysisCode0
ShotVL: Human-Centric Highlight Frame Retrieval via Language Queries—0
CondiMen: Conditional Multi-Person Mesh Recovery—0
Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion—0
A multimodal dataset for understanding the impact of mobile phones on remote online virtual educationCode0
ExeChecker: Where Did I Go Wrong?Code0
Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos—0
FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction—0
RatBodyFormer: Rat Body Surface from Keypoints—0
BLADE: Single-view Body Mesh Learning through Accurate Depth Estimation—0
Show:102550
← PrevPage 8 of 85Next →
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