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 301–350 of 4228 papers

TitleStatusHype
From Image Collections to Point Clouds with Self-supervised Shape and Pose NetworksCode1
Causal Transformer for Fusion and Pose Estimation in Deep Visual Inertial OdometryCode1
EI-Nexus: Towards Unmediated and Flexible Inter-Modality Local Feature Extraction and Matching for Event-Image DataCode1
CattleEyeView: A Multi-task Top-down View Cattle Dataset for Smarter Precision Livestock FarmingCode1
3D/2D Registration of Angiograms using Silhouette-based Differentiable RenderingCode1
Certifiably Optimal Outlier-Robust Geometric Perception: Semidefinite Relaxations and Scalable Global OptimizationCode1
ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D PosesCode1
Ego-Body Pose Estimation via Ego-Head Pose EstimationCode1
Bayesian Uncertainty and Expected Gradient Length -- Regression: Two Sides Of The Same Coin?Code1
EgoHand: Ego-centric Hand Pose Estimation and Gesture Recognition with Head-mounted Millimeter-wave Radar and IMUsCode1
CATRE: Iterative Point Clouds Alignment for Category-level Object Pose RefinementCode1
Absolute Pose from One or Two Scaled and Oriented FeaturesCode1
Efficient Virtual View Selection for 3D Hand Pose EstimationCode1
EgoPoseFormer: A Simple Baseline for Stereo Egocentric 3D Human Pose EstimationCode1
EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the WildCode1
Cascaded Pyramid Network for Multi-Person Pose EstimationCode1
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in SpaceCode1
EfficientPose: Efficient Human Pose Estimation with Neural Architecture SearchCode1
Full-Body Articulated Human-Object InteractionCode1
CaSPR: Learning Canonical Spatiotemporal Point Cloud RepresentationsCode1
EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approachCode1
EfficientPose: Scalable single-person pose estimationCode1
CARLA-BSP: a simulated dataset with pedestriansCode1
Capturing the motion of every joint: 3D human pose and shape estimation with independent tokensCode1
CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose EstimationCode1
CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the WildCode1
PCRNet: Point Cloud Registration Network using PointNet EncodingCode1
CapeX: Category-Agnostic Pose Estimation from Textual Point ExplanationCode1
Cascaded deep monocular 3D human pose estimation with evolutionary training dataCode1
Efficient Solution of Point-Line Absolute PoseCode1
EfficientHRNet: Efficient Scaling for Lightweight High-Resolution Multi-Person Pose EstimationCode1
CAD2Render: A Modular Toolkit for GPU-accelerated Photorealistic Synthetic Data Generation for the Manufacturing IndustryCode1
Efficient Human Pose Estimation via 3D Event Point CloudCode1
Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality SelectionCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Efficient Domain Adaptation via Generative Prior for 3D Infant Pose EstimationCode1
Efficient Initial Pose-graph Generation for Global SfMCode1
A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth ImageCode1
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor ExtractionCode1
Edge Weight Prediction For Category-Agnostic Pose EstimationCode1
BRACE: The Breakdancing Competition Dataset for Dance Motion SynthesisCode1
EdgeRegNet: Edge Feature-based Multimodal Registration Network between Images and LiDAR Point CloudsCode1
A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB ImageCode1
BundleFusion: Real-time Globally Consistent 3D Reconstruction using On-the-fly Surface Re-integrationCode1
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket SportsCode1
Breaking the Frame: Visual Place Recognition by Overlap PredictionCode1
BVMatch: Lidar-based Place Recognition Using Bird's-eye View ImagesCode1
A Mathematical Analysis of Learning Loss for Active Learning in RegressionCode1
CAD-Estate: Large-scale CAD Model Annotation in RGB VideosCode1
Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint EstimatesCode1
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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
4UDP-Pose-PSA(384x288)AP79.5—Unverified
5PoseBH-HAP79.5—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
9CID (HRNet-W48)Test AP45—Unverified
10MaskPose-bTest AP45—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPosePCK99.5—Unverified
2Soft-gated Skip ConnectionsPCK94.8—Unverified
3UniPosePCK94.5—Unverified
4Residual Hourglass + ASR + AHOPCK94.5—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