{
  "abstract": "Two obstacles limit automated behavior analysis in neuroethology: the burden of first training pose estimation models, and the inability to identify behavior quickly enough for real-time classification that could trigger stimuli, drug delivery, or environmental manipulations. Here we present B-REAL, a pose-free classifier that maps raw video to behavior faster than video frames are recorded, even on a CPU. Given substantially less training data, B-REAL matched or surpassed established methods trained on full benchmark rodent or fly datasets, particularly on rare and even single-frame behaviors. Pretraining on unlabeled video further improves its accuracy without slowing inference or training time. In closed loop, rewarding mice for B-REAL-detected grooming more than doubled their performance of grooming bouts. B-REAL thus makes closed-loop behavioral experiments practical with minimal annotation and standard hardware.",
  "abstract_shown": true,
  "affiliations": [
    "Carnegie Mellon University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "name": "A. Eagle"
    },
    {
      "name": "B. Kohler"
    },
    {
      "name": "V. Kamrowski"
    },
    {
      "name": "N. Lingam"
    },
    {
      "name": "R. Li"
    },
    {
      "affs": [
        0
      ],
      "name": "E. A. Yttri"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c7bvw47pgbzsm.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.13.758637",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758637v1.full",
  "id": "c7bvw47pgbzsm",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758637v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "1707|Human Pose and Action Recognition"
    ]
  ],
  "openalex": "W7222993941",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758637v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-13",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/c7bvw47pgbzsm.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:42Z",
      "native_id": "10.64898/2026.10.13.758637",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758637v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "B-REAL: A keypoint-less behavior platform for offline classification and real-time detection",
  "title_text": "B-REAL: A keypoint-less behavior platform for offline classification and real-time detection",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:42Z",
  "url": "https://research.draconitic.com/paper/c7bvw47pgbzsm",
  "venue": "bioRxiv",
  "versions": []
}