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arXiv Computer Vision By Jose Luis Ponton, Alexander Winkler, Ladislav Kavan, Yuting Ye, Petr Kadlecek

STyMo: Fast and Controllable Few-Shot Motion Style Transfer

Read the original on arXiv Computer Vision →

STyMo is a few‑shot motion style transfer method that learns from only seconds of paired data and trains in one to two minutes. It decomposes style into a static posture component and a temporal dynamics component, allowing runtime adjustment of posture intensity, temporal exaggeration, and per‑body‑region style. The approach includes a stylizability gate to avoid artifacts on out‑of‑distribution motions and supports an iterative authoring workflow, with results shown across a range of motion styles and a released dataset for future research.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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