mlsanityData to 14 Oct 2026

HHI-Assist: A Dataset and Benchmark of Human-Human Interaction in Physical Assistance Scenario

arXiv 2509.10096 ↗First posted 12 Sep 2025cs.RO cs.CVcited by 1

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Abstract (arXiv)

The increasing labor shortage and aging population underline the need for assistive robots to support human care recipients. To enable safe and responsive assistance, robots require accurate human motion prediction in physical interaction scenarios. However, this remains a challenging task due to the variability of assistive settings and the complexity of coupled dynamics in physical interactions. In this work, we address these challenges through two key contributions: (1) HHI-Assist, a dataset comprising motion capture clips of human-human interactions in assistive tasks; and (2) a conditional Transformer-based denoising diffusion model for predicting the poses of interacting agents. Our model effectively captures the coupled dynamics between caregivers and care receivers, demonstrating improvements over baselines and strong generalization to unseen scenarios. By advancing interaction-aware motion prediction and introducing a new dataset, our work has the potential to significantly enhance robotic assistance policies. The dataset and code are available at: https://sites.google.com/view/hhi-assist/home

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 38 of its 70 references that are in the map. First posted on arXiv 12 Sep 2025.

Builds on

38 of 70 references.

References · 38

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  12. 2018Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learningcited by 175
26 more
  1. 2020A Spatio-temporal Transformer for 3D Human Motion Predictioncited by 133
  2. 2018Convolutional Sequence to Sequence Model for Human Dynamicscited by 115
  3. 2022Back to MLP: A Simple Baseline for Human Motion Predictioncited by 100
  4. 2017The Pose Knows: Video Forecasting by Generating Pose Futurescited by 88
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  18. 2023Reconstructing Three-Dimensional Models of Interacting Humanscited by 14
  19. 2025WorldPose: A World Cup Dataset for Global 3D Human Pose Estimationcited by 14
  20. 2018Bio-LSTM: A Biomechanically Inspired Recurrent Neural Network for 3D Pedestrian Pose and Gait Predictioncited by 13
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Learning to Assist: Physics-Grounded Human-Human Control via Multi-Agent Reinforcement Learningcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2026Learning Robot Policies for Whole-Body Mobility Assistance via Dynamic Human Motion Generation ↗
  2. 2025Interact2Ar: Full-Body Human-Human Interaction Generation via Autoregressive Diffusion Models
  3. 2023Diffusion Co-Policy for Synergistic Human-Robot Collaborative Tasks
  4. 2022MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction
  5. 2025H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation
  6. 2025REALM: Real-Time Estimates of Assistance for Learned Models in Human-Robot Interaction
  7. 2025Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics
  8. 2025OpenRoboCare: A Multimodal Multi-Task Expert Demonstration Dataset for Robot Caregiving