XmoPipe: A Pipeline for Large-Scale In-the-Wild Human Motion Dataset Construction

arXiv:2606.20731v1 Announce Type: new Abstract: Large-scale human motion datasets are essential for training robust motion models for analysis, synthesis, and understanding. While marker-based motion capture provides precise data, it is costly and limited in scale and diversity. Recent advances in monocular motion capture and video-language understanding open the way to extract plausible motion from unconstrained online videos. We present a scalable pipeline for constructing in-the-wild human mo...

arXiv cs.CV ·Nathan Salazar, Emmanuel Dellandr\'ea, Mathieu Lefort, Alexandre Meyer ·
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