{"slug": "towards-real-world-wearable-motion-reconstruction", "title": "Towards Real-World Wearable Motion Reconstruction", "summary": "Researchers introduced WHIP, a generative model that reconstructs full-body motion from arbitrary subsets of wearable sensors like smartphones and smartwatches, supported by a new multi-modal dataset of 50 activities. The work aims to enable unobtrusive motion capture using consumer devices, addressing the limitation of fixed sensor configurations in prior research.", "body_md": "arXiv:2607.09780v1 Announce Type: new\nAbstract: The modern-day surge in popularity of wearable devices poses a fundamentally unique motion capture problem: reconstructing full-body movement from any set of sensing hardware worn at a given moment. Yet, most research efforts assume fixed sensor configurations (e.g. IMU suits or HMD-centric rigs) and cannot generalize across them. In contrast, we argue that motion capture should prioritize unobtrusive and lightweight devices such as smartphones, smartwatches, smart glasses, and smart insoles, and study the interplay between them. To this end, we make three contributions. First, we present a large-scale multi-modal dataset synchronizing these consumer-grade sensors with ground-truth 3D motion, spanning 50 diverse activities including everyday tasks, sports, and social interactions. Second, we propose WHIP, a baseline generative model that reconstructs motion from arbitrary subsets of available sensors, robustly handling missing modalities and producing physically plausible motions. Third, we conduct a systematic study of sensor complementarity, quantifying how different modalities complement one another. Code and dataset are available at https://vcai.mpi-inf.mpg.de/projects/WHIP/", "url": "https://wpnews.pro/news/towards-real-world-wearable-motion-reconstruction", "canonical_source": "https://arxiv.org/abs/2607.09780", "published_at": "2026-07-14 04:00:00+00:00", "updated_at": "2026-07-14 04:03:41.868108+00:00", "lang": "en", "topics": ["machine-learning", "computer-vision", "ai-research"], "entities": ["WHIP", "MPI Informatics"], "alternates": {"html": "https://wpnews.pro/news/towards-real-world-wearable-motion-reconstruction", "markdown": "https://wpnews.pro/news/towards-real-world-wearable-motion-reconstruction.md", "text": "https://wpnews.pro/news/towards-real-world-wearable-motion-reconstruction.txt", "jsonld": "https://wpnews.pro/news/towards-real-world-wearable-motion-reconstruction.jsonld"}}