SOTAVerified

Pose Tracking

Pose Tracking is the task of estimating multi-person human poses in videos and assigning unique instance IDs for each keypoint across frames. Accurate estimation of human keypoint-trajectories is useful for human action recognition, human interaction understanding, motion capture and animation.

Source: LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–160 of 191 papers

TitleStatusHype
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving—0
TesseTrack: End-to-End Learnable Multi-Person Articulated 3D Pose Tracking—0
Towards Better Robustness: Progressively Joint Pose-3DGS Learning for Arbitrarily Long Videos—0
UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling—0
Variational Inference and Learning of Piecewise-linear Dynamical Systems—0
V-Hands: Touchscreen-based Hand Tracking for Remote Whiteboard Interaction—0
V-HOP: Visuo-Haptic 6D Object Pose Tracking—0
VIPose: Real-time Visual-Inertial 6D Object Pose Tracking—0
Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking—0
Visual Representation Learning with Stochastic Frame Prediction—0
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All datasetsPoseTrack2017PoseTrack2018Multi-Person PoseTrack

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DetTrackMOTA64.09—Unverified
2KeyTrackMOTA61.15—Unverified
3LightTrackMOTA58.01—Unverified
4HRNet-W48 COCOMOTA57.93—Unverified
5MSRA (FlowTrack)MOTA57.81—Unverified
6TML++ (MIPAL)MOTA54.46—Unverified
7STAFMOTA53.81—Unverified
8ProTrackerMOTA51.82—Unverified
9PoseFlowMOTA50.98—Unverified
10PoseTrackMOTA48.37—Unverified
#ModelMetricClaimedVerifiedStatus
1DetTrackMOTA64.3—Unverified
2UniTrackMOTA63.5—Unverified
34DHumans + ViTDetMOTA61.9—Unverified
4MSRAMOTA61.37—Unverified
5TML++ (MIPAL)MOTA54.86—Unverified
#ModelMetricClaimedVerifiedStatus
1PoseTrackMOTA28.2—Unverified