Papers › PoseTrack: A Benchmark for Human Pose Estimation and Tracking

PoseTrack: A Benchmark for Human Pose Estimation and Tracking

27 Oct 2017CVPR 2018 6arXiv:1710.10000archive 2025-07-28

Mykhaylo Andriluka, Umar Iqbal, Eldar Insafutdinov, Leonid Pishchulin, Anton Milan, Juergen Gall, Bernt Schiele

Human poses and motions are important cues for analysis of videos with people and there is strong evidence that representations based on body pose are highly effective for a variety of tasks such as activity recognition, content retrieval and social signal processing. In this work, we aim to further advance the state of the art by establishing "PoseTrack", a new large-scale benchmark for video-based human pose estimation and articulated tracking, and bringing together the community of researchers working on visual human analysis. The benchmark encompasses three competition tracks focusing on i) single-frame multi-person pose estimation, ii) multi-person pose estimation in videos, and iii) multi-person articulated tracking. To facilitate the benchmark and challenge we collect, annotate and release a new %large-scale benchmark dataset that features videos with multiple people labeled with person tracks and articulated pose. A centralized evaluation server is provided to allow participants to evaluate on a held-out test set. We envision that the proposed benchmark will stimulate productive research both by providing a large and representative training dataset as well as providing a platform to objectively evaluate and compare the proposed methods. The benchmark is freely accessible at https://posetrack.net.

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Code

ken724049/action-recognition mentioned on GitHub report
open-mmlab/mmpose pytorchApache-2.0 report

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Tasks

Activity RecognitionMulti-Person Pose EstimationPose EstimationPose TrackingRetrieval

Datasets

Introduced by this paper, per the archive.

PoseTrack

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Multi-Person Pose Estimation PoseTrack2017 PoseTrack Mean mAP 59.4 #3 of 3 Archive leaderboard report
Pose Tracking PoseTrack2017 PoseTrack MOTA 48.37 #10 of 10 Archive leaderboard report
Pose Tracking PoseTrack2017 PoseTrack mAP 59.22 #10 of 10 Archive leaderboard report

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