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 1601–1650 of 4228 papers

TitleStatusHype
Domain-Adaptive 2D Human Pose Estimation via Dual Teachers in Extremely Low-Light ConditionsCode0
RADA: Robust and Accurate Feature Learning with Domain Adaptation—0
Local Occupancy-Enhanced Object Grasping with Multiple Triplanar Projection—0
ESCAPE: Energy-based Selective Adaptive Correction for Out-of-distribution 3D Human Pose Estimation—0
SCAPE: A Simple and Strong Category-Agnostic Pose EstimatorCode0
RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark—0
Invertible Neural Warp for NeRF—0
Monocular pose estimation of articulated surgical instruments in open surgery—0
Deep-Learning-Based Markerless Pose Estimation Systems in Gait Analysis: DeepLabCut Custom Training and the Refinement Function—0
Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis—0
GTPT: Group-based Token Pruning Transformer for Efficient Human Pose Estimation—0
3D Foundation Models Enable Simultaneous Geometry and Pose Estimation of Grasped Objects—0
3DEgo: 3D Editing on the Go!—0
STGFormer: Spatio-Temporal GraphFormer for 3D Human Pose Estimation in Video—0
psifx -- Psychological and Social Interactions Feature Extraction Package—0
Emotion Detection through Body Gesture and Face—0
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental LearningCode0
KGpose: Keypoint-Graph Driven End-to-End Multi-Object 6D Pose Estimation via Point-Wise Pose Voting—0
HUP-3D: A 3D multi-view synthetic dataset for assisted-egocentric hand-ultrasound pose estimation—0
RTMW: Real-Time Multi-Person 2D and 3D Whole-body Pose Estimation—0
Hybrid Structure-from-Motion and Camera Relocalization for Enhanced Egocentric LocalizationCode0
Greit-HRNet: Grouped Lightweight High-Resolution Network for Human Pose Estimation—0
Computer vision tasks for intelligent aerospace missions: An overview—0
Category-level Object Detection, Pose Estimation and Reconstruction from Stereo Images—0
GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields—0
Unsupervised Learning of Category-Level 3D Pose from Object-Centric VideosCode0
Towards Cross-View-Consistent Self-Supervised Surround Depth EstimationCode0
Markerless Multi-view 3D Human Pose Estimation: a survey—0
Graph and Skipped Transformer: Exploiting Spatial and Temporal Modeling Capacities for Efficient 3D Human Pose Estimation—0
SUPER: Seated Upper Body Pose Estimation using mmWave Radars—0
Joint-Dataset Learning and Cross-Consistent Regularization for Text-to-Motion Retrieval—0
Active Human Pose Estimation via an Autonomous UAV Agent—0
Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review—0
EPOCH: Jointly Estimating the 3D Pose of Cameras and Humans—0
Human Modelling and Pose Estimation Overview—0
Towards Human-Level 3D Relative Pose Estimation: Generalizable, Training-Free, with Single ReferenceCode0
Automatic infant 2D pose estimation from videos: comparing seven deep neural network methods—0
High-resolution open-vocabulary object 6D pose estimation—0
Investigating the impact of 2D gesture representation on co-speech gesture generation—0
Efficient Human Pose Estimation: Leveraging Advanced Techniques with MediaPipeCode0
PoseBench: Benchmarking the Robustness of Pose Estimation Models under Corruptions—0
Benchmarking Monocular 3D Dog Pose Estimation Using In-The-Wild Motion Capture Data—0
An Efficient yet High-Performance Method for Precise Radar-Based Imaging of Human Hand Poses—0
CNN Based Flank Predictor for Quadruped Animal Species—0
NeRF-Feat: 6D Object Pose Estimation using Feature Rendering—0
MVSBoost: An Efficient Point Cloud-based 3D Reconstruction—0
Head Pose Estimation and 3D Neural Surface Reconstruction via Monocular Camera in situ for Navigation and Safe Insertion into Natural Openings—0
Overlap Suppression Clustering for Offline Multi-Camera People Tracking—0
Matching Query Image Against Selected NeRF Feature for Efficient and Scalable Localization—0
Domain Generalization for In-Orbit 6D Pose Estimation—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