{
  "id": 11994,
  "url": "https://arxiv.org/abs/2607.17342v1",
  "title": "STAR: Skeletal Token Alignment and Rearrangement for Interaction Recognition",
  "summary": "Understanding physical human-robot and human-human interactions is a challenging yet emerging topic in 3D vision. While most existing methods rely on skeleton sequences--effective in low-light and privacy-sensitive environment--they face two major challenges: 1) learning and effectively exploiting interaction cues from skeletal data, and 2) compensating for the lack of visual information absent in skeletons alone. To address these challenges, we propose skeletal token alignment and rearrangement",
  "authors": "Yuhang Wen, Mengyuan Liu, Zixuan Tang, Junsong Yuan, Sirui Li, Beichen Ding",
  "category": "research",
  "topics": "safety-alignment,privacy-surveillance,agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-19T17:05:46.000Z",
  "fetched_at": "2026-07-21T05:10:12.656Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/11994",
  "original_url": "https://arxiv.org/abs/2607.17342v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}