How Do I Do That? Synthesizing 3D Hand Motion and Contacts for Everyday Interactions
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Abstract (arXiv)
We tackle the novel problem of predicting 3D hand motion and contact maps (or Interaction Trajectories) given a single RGB view, action text, and a 3D contact point on the object as input. Our approach consists of (1) Interaction Codebook: a VQVAE model to learn a latent codebook of hand poses and contact points, effectively tokenizing interaction trajectories, (2) Interaction Predictor: a transformer-decoder module to predict the interaction trajectory from test time inputs by using an indexer module to retrieve a latent affordance from the learned codebook. To train our model, we develop a data engine that extracts 3D hand poses and contact trajectories from the diverse HoloAssist dataset. We evaluate our model on a benchmark that is 2.5-10X larger than existing works, in terms of diversity of objects and interactions observed, and test for generalization of the model across object categories, action categories, tasks, and scenes. Experimental results show the effectiveness of our approach over transformer & diffusion baselines across all settings.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 45 of its 55 references that are in the map. First posted on arXiv 16 Apr 2025.
Builds on
45 of 55 references.
References · 45
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33 more
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Built on by
Citing papers per year: 2025: 6; 2026: 4.
10 papers.
- 2025OpenHOI: Open-World Hand-Object Interaction Synthesis with Multimodal Large Language Modelcited by 17
- 2025Learning Dense Hand Contact Estimation from Imbalanced Datacited by 14
- 2026LOME: Learning Human-Object Manipulation with Action-Conditioned Egocentric World Modelcited by 13
- 2025MEgoHand: Multimodal Egocentric Hand-Object Interaction Motion Generationcited by 9
- 2025Building Egocentric Procedural AI Assistant: Methods, Benchmarks, and Challengescited by 5
- 2026PAM: A Pose-Appearance-Motion Engine for Sim-to-Real HOI Video Generationcited by 3
- 2025Affordance-Guided Diffusion Prior for 3D Hand Reconstructioncited by 2
- 2026HOPE: Hand-Object Pressure Estimation from Monocular Videoscited by 2
- 2025Bimanual 3D Hand Motion and Articulation Forecasting in Everyday Imagescited by 1
- 2026Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfercited by 1
- 2026HOPE: Hand-Object Pressure Estimation from Monocular Videos6 Aug 2026
- 2026Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer30 Jul 2026
- 2026LOME: Learning Human-Object Manipulation with Action-Conditioned Egocentric World Model28 Mar 2026
- 2026PAM: A Pose-Appearance-Motion Engine for Sim-to-Real HOI Video Generation23 Mar 2026
- 2025Building Egocentric Procedural AI Assistant: Methods, Benchmarks, and Challenges17 Nov 2025
- 2025Bimanual 3D Hand Motion and Articulation Forecasting in Everyday Images7 Oct 2025
- 2025Affordance-Guided Diffusion Prior for 3D Hand Reconstruction1 Oct 2025
- 2025OpenHOI: Open-World Hand-Object Interaction Synthesis with Multimodal Large Language Model25 May 2025
- 2025MEgoHand: Multimodal Egocentric Hand-Object Interaction Motion Generation22 May 2025
- 2025Learning Dense Hand Contact Estimation from Imbalanced Data16 May 2025