{"ID":2854331,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.16258","arxiv_id":"2510.16258","title":"Embody 3D: A Large-scale Multimodal Motion and Behavior Dataset","abstract":"The Codec Avatars Lab at Meta introduces Embody 3D, a multimodal dataset of 500 individual hours of 3D motion data from 439 participants collected in a multi-camera collection stage, amounting to over 54 million frames of tracked 3D motion. The dataset features a wide range of single-person motion data, including prompted motions, hand gestures, and locomotion; as well as multi-person behavioral and conversational data like discussions, conversations in different emotional states, collaborative activities, and co-living scenarios in an apartment-like space. We provide tracked human motion including hand tracking and body shape, text annotations, and a separate audio track for each participant.","short_abstract":"The Codec Avatars Lab at Meta introduces Embody 3D, a multimodal dataset of 500 individual hours of 3D motion data from 439 participants collected in a multi-camera collection stage, amounting to over 54 million frames of tracked 3D motion. The dataset features a wide range of single-person motion data, including promp...","url_abs":"https://arxiv.org/abs/2510.16258","url_pdf":"https://arxiv.org/pdf/2510.16258v1","authors":"[\"Claire McLean\",\"Makenzie Meendering\",\"Tristan Swartz\",\"Orri Gabbay\",\"Alexandra Olsen\",\"Rachel Jacobs\",\"Nicholas Rosen\",\"Philippe de Bree\",\"Tony Garcia\",\"Gadsden Merrill\",\"Jake Sandakly\",\"Julia Buffalini\",\"Neham Jain\",\"Steven Krenn\",\"Moneish Kumar\",\"Dejan Markovic\",\"Evonne Ng\",\"Fabian Prada\",\"Andrew Saba\",\"Siwei Zhang\",\"Vasu Agrawal\",\"Tim Godisart\",\"Alexander Richard\",\"Michael Zollhoefer\"]","published":"2025-10-17T23:06:36Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}