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

Showing 151–175 of 191 papers

TitleStatusHype
Efficient Circle-Based Camera Pose Tracking Free of PnP—0
Movement science needs different pose tracking algorithms—0
Large-scale, real-time visual-inertial localization revisited—0
Pose estimator and tracker using temporal flow maps for limbs—0
PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose TrackingCode0
Low-latency Visual SLAM with Appearance-Enhanced Local Map Building—0
LightTrack: A Generic Framework for Online Top-Down Human Pose TrackingCode0
Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking—0
Multigrid Predictive Filter Flow for Unsupervised Learning on VideosCode0
Multi-person Articulated Tracking with Spatial and Temporal Embeddings—0
Human Pose Estimation using Motion Priors and Ensemble Models—0
A Top-down Approach to Articulated Human Pose Estimation and Tracking—0
Efficient Online Multi-Person 2D Pose Tracking with Recurrent Spatio-Temporal Affinity Fields—0
Explicit Spatiotemporal Joint Relation Learning for Tracking Human Pose—0
Deep Model-Based 6D Pose Refinement in RGBCode0
Good Line Cutting: towards Accurate Pose Tracking of Line-assisted VO/VSLAM—0
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving—0
A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object TrackingCode0
Robust pose tracking with a joint model of appearance and shape—0
PoseFlow: A Deep Motion Representation for Understanding Human Behaviors in Videos—0
Joint Flow: Temporal Flow Fields for Multi Person Tracking—0
Efficient Pose Tracking from Natural Features in Standard Web Browsers—0
Learning to Refine Human Pose Estimation—0
Statistical Sensor Fusion of a 9-DoF MEMS IMU for Indoor Navigation—0
Pose Flow: Efficient Online Pose TrackingCode0
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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