HumanTracker: A Human-Aligned Benchmark for Humanoid Motion Tracking Evaluation

Forum topic · 小凯 · 2026-08-15

Summary

HumanTracker is a new benchmark and metric for evaluating humanoid motion tracking, addressing the gap between kinematic error metrics and human perception. Kinematic errors average per-frame pose differences but miss critical physical artifacts like unstable support, foot skating, and mistimed touch-downs, while existing test suites are small and lack diversity. The HumanTracker benchmark contains approximately 153 hours of optical motion trajectories from multiple professional performers, organized into four motion families with text labels for fine-grained diagnosis. The authors also propose HumanScore, a preference-aligned metric trained on 12K motion pairs containing 24K motions. Across representative state-of-the-art trackers, HumanScore better predicts human preferences and reveals contact and stability failures that kinematic metrics often miss, making humanoid tracking evaluation both perceptually aligned and scalable.

Paper Overview

Research Area: Computer Vision (CV)

Authors: Dairu Liu, Zekun Qi, Jiayu Zeng, Ruixi Yu, Yu Guan, Yintianrun Zhang, Xuchuan Chen, Sikai Liang, Zekai Li, Chenghuai Lin, Xinqiang Yu, Wenyao Zhang, He Wang, Li Yi

arXiv: 2608.13555

Abstract

Humanoid motion tracking is central to teleoperation and whole-body imitation, yet evaluation often disagrees with what people perceive in videos. Kinematic errors average per-frame pose differences but miss the physical artifacts that matter most, particularly unstable support and incorrect contacts such as foot skating and mistimed touch-downs. Meanwhile, widely used test suites are small and lack the diversity needed to stress contact-rich, long-horizon behaviors.

Key Contributions

HumanTracker Benchmark: Contains approximately 153 hours of optical motion trajectories from multiple professional performers, organized into four motion families with text labels for fine-grained diagnosis.
HumanScore Metric: A preference-aligned metric trained on 12K motion pairs containing 24K motions.

Results

Across representative state-of-the-art trackers, HumanScore better predicts human preferences and reveals contact and stability failures that kinematic metrics often miss, making humanoid tracking evaluation both perceptually aligned and scalable.

---

*Auto-collected on 2026-08-15*