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

Showing 19011950 of 4228 papers

TitleStatusHype
Learning-based Monocular 3D Reconstruction of Birds: A Contemporary Survey0
Multi-person 3D pose estimation from a single image captured by a fisheye camera0
Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video SnippetCode1
PoseGU: 3D Human Pose Estimation with Novel Human Pose Generator and Unbiased Learning0
Vision Transformers: State of the Art and Research Challenges0
Unsupervised Learning for Human Sensing Using Radio Signals0
Semi-supervised Human Pose Estimation in Art-historical ImagesCode0
FewSOL: A Dataset for Few-Shot Object Learning in Robotic EnvironmentsCode0
Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimation0
DPODv2: Dense Correspondence-Based 6 DoF Pose Estimation0
Semi-Perspective Decoupled Heatmaps for 3D Robot Pose Estimation from Depth Maps0
3D Part Assembly Generation with Instance Encoded Transformer0
PVO: Panoptic Visual OdometryCode2
Drift Reduction for Monocular Visual Odometry of Intelligent Vehicles using Feedforward Neural Networks0
How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video Depth ForecastingCode0
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy0
Vision-based Conflict Detection within Crowds based on High-Resolution Human Pose Estimation for Smart and Safe Airport0
Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset0
BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDAR0
3D Multi-Object Tracking with Differentiable Pose Estimation0
Improving Worst Case Visual Localization Coverage via Place-specific Sub-selection in Multi-camera Systems0
Deep Optical Coding Design in Computational Imaging0
A View Independent Classification Framework for Yoga Postures0
Optimal and Robust Category-level Perception: Object Pose and Shape Estimation from 2D and 3D Semantic KeypointsCode0
HM3D-ABO: A Photo-realistic Dataset for Object-centric Multi-view 3D ReconstructionCode1
Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation0
CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal PoseCode1
Unseen Object 6D Pose Estimation: A Benchmark and Baselines0
BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation0
I^2R-Net: Intra- and Inter-Human Relation Network for Multi-Person Pose EstimationCode1
Certifiable 3D Object Pose Estimation: Foundations, Learning Models, and Self-TrainingCode1
0/1 Deep Neural Networks via Block Coordinate Descent0
Embodied Scene-aware Human Pose Estimation0
Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks0
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry0
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation0
Self-Supervised Learning of Image Scale and OrientationCode1
TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose EstimationCode1
Category-Agnostic 6D Pose Estimation with Conditional Neural Processes0
A Training Method For VideoPose3D With Ideology of Action Recognition0
GraphMLP: A Graph MLP-Like Architecture for 3D Human Pose EstimationCode1
Estimating Pose from Pressure Data for Smart Beds with Deep Image-based Pose Estimators0
APT-36K: A Large-scale Benchmark for Animal Pose Estimation and TrackingCode1
E2PN: Efficient SE(3)-Equivariant Point NetworkCode1
Ego2HandsPose: A Dataset for Egocentric Two-hand 3D Global Pose Estimation0
Building Spatio-temporal Transformers for Egocentric 3D Pose Estimation0
Efficient Human Pose Estimation via 3D Event Point CloudCode1
Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D ConvolutionsCode2
Unsupervised Learning of 3D Scene Flow from Monocular CameraCode0
PixSelect: Less but Reliable Pixels for Accurate and Efficient Localization0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1yoloposeAP5090.3Unverified
2ViTPose (ViTAE-G, ensemble)AP81.1Unverified
3ViTPose (ViTAE-G)AP80.9Unverified
4UDP-Pose-PSA(384x288)AP79.5Unverified
5PoseBH-HAP79.5Unverified
64xRSN-50 (ensemble)AP79.2Unverified
7UDP-Pose-PSA(256x192)AP78.9Unverified
8CCM+AP78.9Unverified
94xRSN-50AP78.6Unverified
10PCT (256x256)AP78.3Unverified
#ModelMetricClaimedVerifiedStatus
1PCT (swin-l, test set)PCKh-0.594.3Unverified
2Soft-gated Skip ConnectionsPCKh-0.594.1Unverified
3Cascade Feature AggregationPCKh-0.593.9Unverified
4PCT (swin-b, test set)PCKh-0.593.8Unverified
5TransPosePCKh-0.593.5Unverified
6UniHCP (FT)PCKh-0.593.2Unverified
74xRSN-50PCKh-0.593Unverified
8UniPosePCKh-0.592.7Unverified
9MSPNPCKh-0.592.6Unverified
10Spatial ContextPCKh-0.592.5Unverified
#ModelMetricClaimedVerifiedStatus
1ViTPose (ViTAE-G, GT bounding boxes)Test AP93.3Unverified
2UniHCP (direct eval)Test AP87.4Unverified
3PoseBH-HTest AP87Unverified
4RTMPose(RTMPose-l, GT bounding boxes)Test AP80.3Unverified
5TransPose-HValidation AP62.3Unverified
6BBox-Mask-Pose 2xTest AP48.3Unverified
7BUCTD (CID-W32)Test AP47.2Unverified
8HQNet (ViT-L)Test AP45.6Unverified
9CID (HRNet-W48)Test AP45Unverified
10MaskPose-bTest AP45Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPosePCK99.5Unverified
2Soft-gated Skip ConnectionsPCK94.8Unverified
3UniPosePCK94.5Unverified
4Residual Hourglass + ASR + AHOPCK94.5Unverified
5Chou et al. arXiv'17PCK94Unverified
6Pyramid Residual Modules (PRMs)PCK93.9Unverified
7Stacked hourglass + Inception-resnetPCK93.9Unverified
8Multi-Context AttentionPCK92.6Unverified
9FPDPCK90.8Unverified
10Part heatmap regression (ResNet-152)PCK90.7Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD-W48 (w/cond. input from PETR, and generative sampling)AP78.5Unverified
2ViTPose-GAP78.3Unverified
3BUCTD-W48 (w/cond. input from PETR)AP76.7Unverified
4SwinV2-L 1K-MIMAP75.5Unverified
5SwinV2-B 1K-MIMAP74.9Unverified
6BUCTD-W48AP72.9Unverified
7OpenPifPafAP70.5Unverified
8MIPNet (HRNet-W48)AP70Unverified
9KAPAO-LAP68.9Unverified
10KAPAO-MAP67.1Unverified
#ModelMetricClaimedVerifiedStatus
1CCNet (ViTPose-B_GT-bbox_256x192)AP78.1Unverified
2MogaNet-B (384x288)AP77.3Unverified
3ViTPose-B (Single-task_GT-bbox_256x192)AP77.3Unverified
4MogaNet-S (384x288)AP76.4Unverified
5Bias (HRNet_256x192)AP75.8Unverified
6ViTPose-B (Single-task_Det-bbox_256x192)AP75.8Unverified
7HRNet (256x192)AP75.3Unverified
8MogaNet-S (256x192)AP74.9Unverified
9MogaNet-T (256x192)AP73.2Unverified
10RLE (256x192)AP71.3Unverified
#ModelMetricClaimedVerifiedStatus
1Hulk(Finetune, ViT-L)AP37.1Unverified
2Hulk(Finetune, ViT-B)AP35.6Unverified
3HRFormer (HRFomer-B)AP34.4Unverified
4UniHCP (finetune)AP33.6Unverified
5HRNet (HRNet-w48 )AP33.5Unverified
6HRNet (HRNet-w32)AP32.3Unverified
7HRFormer (HRFomer-S)AP31.6Unverified
8SimpleBaseline (ResNet-152)AP29.9Unverified
9SimpleBaseline (ResNet-101)AP29.4Unverified
10SimpleBaseline (ResNet-50)AP28Unverified
#ModelMetricClaimedVerifiedStatus
1BUCTD (PETR, with generative sampling)APL83.7Unverified
2OmniPose (WASPv2)AP79.5Unverified
3MetaPrompt-SDAP79Unverified
4Hulk(Finetune, ViT-L)AP78.7Unverified
5BUCTD (PETR, with generative sampling)AP77.8Unverified
6Hulk(Finetune, ViT-B)AP77.5Unverified
7I²R-Net (1st stage:HRFormer-B)AP77.3Unverified
8PATH (Partial FT)AP77.1Unverified
9SOLIDER (swin-B)AP76.6Unverified
10PEFORMER-Xcit-dino-p8AP72.6Unverified
#ModelMetricClaimedVerifiedStatus
1GIM-DKMDUC1-Acc@0.25m,10°57.1Unverified
2GIM-LoFTRDUC1-Acc@0.25m,10°54.5Unverified
3GIM-SuperGlueDUC1-Acc@0.25m,10°53.5Unverified
4DKMDUC1-Acc@0.25m,10°51.5Unverified
5SuperGlueDUC1-Acc@0.25m,10°49Unverified
6LoFTRDUC1-Acc@0.25m,10°47.5Unverified
#ModelMetricClaimedVerifiedStatus
1AdaPoseMean mAP93.38Unverified
2DECA-D3Mean mAP88.75Unverified
3V2V-PoseNetMean mAP88.74Unverified
4A2JMean mAP88Unverified
5RENMean mAP84.9Unverified
6Multi-task learning + viewpoint invarianceMean mAP77.4Unverified
#ModelMetricClaimedVerifiedStatus
1SimpleBaseline + HANetMean PCK@0.299.6Unverified
2DeciWatchMean PCK@0.299Unverified
3LSTM PMMean PCK@0.293.6Unverified
4CPMMean PCK@0.291.9Unverified
5UniTrack_i18Mean PCK@0.280.5Unverified
#ModelMetricClaimedVerifiedStatus
14xRSN-50PCKh@0.593Unverified
2RefinePCKh@0.592.1Unverified
3EfficientPose IVPCKh@0.591.2Unverified
4OpenPosePCKh@0.588.8Unverified
5Adversarial LearningPCKh@0.588.6Unverified
#ModelMetricClaimedVerifiedStatus
1OmniPoseMean PCK@0.299.4Unverified
2UniPose-LSTMMean PCK@0.299.3Unverified
3LSTM PMMean PCK@0.297.7Unverified
4Thin-SlicingMean PCK@0.296.5Unverified
5Iqbal et al.Mean PCK@0.281.1Unverified
#ModelMetricClaimedVerifiedStatus
1DP-RCNN-DeepLab (ResNet-101)AP68Unverified