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Representative Papers

HumanTracker: Towards Comprehensive and Human-Aligned Motion Tracking Benchmark

Aug 13, 2026

Existing evaluations of humanoid motion tracking rely primarily on kinematic errors, which fail to capture physically implausible distortions perceptible to humans—such as foot sliding or incorrect contact—and suffer from small-scale, low-diversity test sets. To address these limitations, this work introduces HumanTracker, a large-scale and diverse benchmark comprising 153 hours of optical motion capture data from professional actors, covering four action categories with accompanying textual annotations. Furthermore, the authors propose HumanScore, a human-aligned evaluation metric derived from a preference model trained on 12K motion pairs (24K individual motions). HumanScore enables fine-grained diagnosis of critical physical properties like contact fidelity and support stability, significantly outperforming conventional metrics across multiple state-of-the-art trackers, accurately predicting human preferences, and uncovering previously overlooked physical inconsistencies.

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Latest Papers

HumanTracker: Towards Comprehensive and Human-Aligned Motion Tracking Benchmark

Aug 13, 2026

Existing evaluations of humanoid motion tracking rely primarily on kinematic errors, which fail to capture physically implausible distortions perceptible to humans—such as foot sliding or incorrect contact—and suffer from small-scale, low-diversity test sets. To address these limitations, this work introduces HumanTracker, a large-scale and diverse benchmark comprising 153 hours of optical motion capture data from professional actors, covering four action categories with accompanying textual annotations. Furthermore, the authors propose HumanScore, a human-aligned evaluation metric derived from a preference model trained on 12K motion pairs (24K individual motions). HumanScore enables fine-grained diagnosis of critical physical properties like contact fidelity and support stability, significantly outperforming conventional metrics across multiple state-of-the-art trackers, accurately predicting human preferences, and uncovering previously overlooked physical inconsistencies.

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