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New CoMind dataset captures collaborative human activity for AI research

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced CoMind, a novel dataset designed to study human collaboration by capturing real-world cooking scenarios. This dataset integrates multi-perspective video, audio, gaze tracking, and 3D scans, annotated with details on shared attention, social cues, and agent-object interactions. CoMind aims to facilitate research into the cognitive processes supporting collaboration, particularly Theory of Mind, and establishes benchmarks for tasks like Joint Attention Estimation and Collaborative Handover Prediction. AI

IMPACT Enables development and evaluation of AI systems capable of modeling complex social interactions and reasoning about human behaviors in collaborative environments.

RANK_REASON The cluster contains a research paper introducing a new dataset and benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New CoMind dataset captures collaborative human activity for AI research

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The cluster contains a research paper introducing a new dataset and benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Alexey Gavryushin, Dingxi Zhang, Zhao Huang, Alexandros Delitzas, Jiaqi Chen, Ben Ellis, Cedric Z\"ollner, Manthan Patel, Manuel Kaufmann, Marc Pollefeys, Xi Wang ·

    CoMind: Understanding Collaborative Human Activity from Multiple Minds and Views

    arXiv:2607.06691v1 Announce Type: new Abstract: Human-human collaboration is a fundamental aspect of everyday life, essential to success in a wide range of goal-directed activities from household tasks to professional teamwork. While much research has focused on modeling coordina…

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