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Hand-object interaction generation

Generates 3D hand-object and grasp motion with contact guidance and diffusion models.

116 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2019–2026) · an approach in 3D generation, keyword cluster “motion · interaction · human”

State History Tried Baselines Checklist Preprints Who Export

Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

35 papers in 2023–24 and 75 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic grew, from 7.7% to 8.5%.

Open questions the data points to

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

2016: 0162017: 0172018: 0182019: 2192020: 0202021: 0212022: 4222023: 9232024: 26242025: 24252026: 5126

Most cited paper of each year

Earliest papers here

What has been tried

62 papers here report 594 measured changes (a component added, removed or swapped, compared with a baseline): helped 81%, no clear effect 3%, hurt 14%, mixed 2%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
add one VQ-VAE for full-body movementsBEATv1.3 · FGD13.080 -> 9.787HelpedEMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling (CVPR 2024 · 79 citations)
add human-object-contact cross-attentionBEHAVE and CHAIRS · R-Prec. (top-3)0.35 -> 0.62; 0.49 -> 0.74HelpedCG-HOI: Contact-Guided 3D Human-Object Interaction Generation (CVPR 2024 · 48 citations)
Combine guide-pose conditioning with audio conditioning in pose diffusionConversation test set · FDg3.94 -> 2.94HelpedFrom Audio to Photoreal Embodiment: Synthesizing Humans in Conversations (CVPR 2024 · 44 citations)
Add joint hand modeling to the object reconstructionHO3D-v3 · CD [cm2]0.41 -> 0.38HelpedHOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video (CVPR 2024 · 37 citations)
add frame-wise and agent-wise positional encodingGRAB · Physical realism0.8024 ± 0.0007 -> 0.8312 ± 0.0005HelpedText2HOI: Text-guided 3D Motion Generation for Hand-Object Interaction (CVPR 2024 · 34 citations)
use an offset-vector interaction field rather than a scalar-distance fieldSitting · D2O ≤2cm (%)80.9 -> 99.6HelpedNIFTY: Neural Object Interaction Fields for Guided Human Motion Synthesis (CVPR 2024 · 31 citations)
Add global attention (GA) to the full modelPartNet-Mobility test set (K=32) · MMD (ID)0.053 -> 0.049HelpedCAGE: Controllable Articulation GEneration (CVPR 2024 · 22 citations)
add flow information to the inputt0 · success rate31.66 -> 41.43; 9.77% decrease without flowHelpedGenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation Demonstration and Imitation (CVPR 2024 · 19 citations)
remove optimization and use the conditional denoised output directlyFlickrCI3D Signatures · joint PA-MPJPE (mm)66 -> 92HurtGenerative Proxemics: A Prior for 3D Social Interaction from Images (CVPR 2024 · 19 citations)
Add interaction-environment inputs to the grasp synthesizerS1 & S3 · Contact ratio (%)76.27 -> 82.86HelpedTACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding (CVPR 2024 · 19 citations)
Jointly model hand and object rather than condition on hand poseHOI4D · MPJPE1.14 -> 1.05HelpedG-HOP: Generative Hand-Object Prior for Interaction Reconstruction and Grasp Synthesis (CVPR 2024 · 18 citations)
Add estimated normal mapsDexYCB synthesis (1k images) · FID82.40 -> 77.64HelpedHOIDiffusion: Generating Realistic 3D Hand-Object Interaction Data (CVPR 2024 · 18 citations)

Baseline numbers that disagree

The same baseline on the same benchmark and metric, reported more than 5% apart by different papers here. Training budgets, data splits and reimplementations differ, so state which number you compare with.

BaselineBenchmarkMetricReportedPapers
MOHODexYCBF-50.119 – 0.62 papers, e.g. CVPR 2025 and AAAI 2025
MOHODexYCBF-100.249 – 0.812 papers, e.g. CVPR 2025 and AAAI 2025

What reviewers will expect

Datasets and baselines named in the 33 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Datasets

  • GRAB · 5 of 33 papers
  • ARCTIC · 5 of 33 papers
  • BEHAVE · 4 of 33 papers
  • HO3D · 3 of 33 papers
  • DexYCB · 2 of 33 papers
  • PartNet · 2 of 33 papers
  • ShapeNet · 2 of 33 papers
  • InterCap · 2 of 33 papers

Baselines

  • MDM · 4 of 33 papers
  • CHOIS · 4 of 33 papers
  • OMOMO · 3 of 33 papers
  • GraspTTA · 3 of 33 papers
  • InterDiff · 3 of 33 papers
  • PHOSA · 3 of 33 papers
  • IMoS · 2 of 33 papers
  • iHOI · 2 of 33 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 110 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 30 key papersOpen the topic in the interactive map

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    Same keyword cluster

    Elsewhere in the topic

    Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).

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