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2D Pose Estimation

detective pose

Papers

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Showing 51–75 of 90 papers

TitleStatusHype
Multi-Scale Networks for 3D Human Pose Estimation with Inference Stage Optimization—0
Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation—0
Efficient Vision Transformer for Human Pose Estimation via Patch Selection—0
Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation—0
Transformers with Joint Tokens and Local-Global Attention for Efficient Human Pose Estimation—0
Unconstrained Monocular 3D Human Pose Estimation by Action Detection and Cross-Modality Regression Forest—0
Disentangling Pose from Appearance in Monochrome Hand Images—0
CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx—0
Cascaded Pyramid Network for 3D Human Pose Estimation Challenge—0
QuickPose: Real-time Multi-view Multi-person Pose Estimation in Crowded Scenes—0
A Dual-Source Approach for 3D Pose Estimation from a Single Image—0
CapeLLM: Support-Free Category-Agnostic Pose Estimation with Multimodal Large Language Models—0
Removing the Bias of Integral Pose Regression—0
Bottom-Up 2D Pose Estimation via Dual Anatomical Centers for Small-Scale Persons—0
Automatic infant 2D pose estimation from videos: comparing seven deep neural network methods—0
A Dual-Source Approach for 3D Human Pose Estimation from a Single Image—0
ZebraPose: Zebra Detection and Pose Estimation using only Synthetic Data—0
A review of 3D human pose estimation algorithms for markerless motion capture—0
Self-Improving Visual Odometry—0
JointsGait:A model-based Gait Recognition Method based on Gait Graph Convolutional Networks and Joints Relationship Pyramid Mapping—0
3D Pictorial Structures for Multiple View Articulated Pose Estimation—0
A Greedy Part Assignment Algorithm for Real-time Multi-person 2D Pose Estimation—0
3D Human Pose Estimation Using Convolutional Neural Networks with 2D Pose Information—0
SwimXYZ: A large-scale dataset of synthetic swimming motions and videos—0
SyDog: A Synthetic Dog Dataset for Improved 2D Pose Estimation—0
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All datasetsiRodentMP-100300WAnimal KingdomDesert LocustHARPERHuman3.6MMacaquePoseVinegar Fly

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1fine-tuned HRNetw32 pretrained on SuperAnimal (1 fac of data)Average mAP72.97—Unverified
2fine-tuned HRNetw32 pretrained on AP-10K (1 fac of data)Average mAP61.64—Unverified
3fine-tuned HRNetw32 pretrained on SuperAnimal (0.01 fac of data)Average mAP60.85—Unverified
4fine-tuned HRNetw32 pretrained on ImageNetAverage mAP58.86—Unverified
5zero-shot HRNet-w32 pretrained on SuperAnimal-QuadrupedAverage mAP58.56—Unverified
6zero-shot AnimalTokenPose pretrained on AP-10KAverage mAP55.42—Unverified
7fine-tuned HRNetw32 pretrained on AP-10K (0.01 fac of data)Average mAP43.14—Unverified
8zero-shot HRNet-w32 pretrained on AP-10KAverage mAP40.39—Unverified
#ModelMetricClaimedVerifiedStatus
1CapeLLMMean PCK@0.2 - 1shot92.6—Unverified
2CapeXMean PCK@0.2 - 1shot91.5—Unverified
3EdgeCapeMean PCK@0.2 - 1shot89.01—Unverified
4PoseAnything-TMean PCK@0.2 - 1shot87.47—Unverified
5CapeFormerMean PCK@0.2 - 1shot85.31—Unverified
6POMNetMean PCK@0.2 - 1shot79.7—Unverified
#ModelMetricClaimedVerifiedStatus
1UniPoseMean PCK@0.299.4—Unverified
#ModelMetricClaimedVerifiedStatus
1UniPoseMean PCK@0.296.1—Unverified
#ModelMetricClaimedVerifiedStatus
1UniPoseMean PCK@0.299.9—Unverified
#ModelMetricClaimedVerifiedStatus
1HRNetPCK868—Unverified
#ModelMetricClaimedVerifiedStatus
1UniHCP (finetune)EPE6.6—Unverified
#ModelMetricClaimedVerifiedStatus
1UniPoseAP79.4—Unverified
#ModelMetricClaimedVerifiedStatus
1UniPoseMean PCK@0.299.9—Unverified