mlsanityData to 7 Oct 2026

Action2Motion: Conditioned Generation of 3D Human Motions

arXiv 2007.15240 ↗First posted 30 Jul 2020cs.CVcited by 438

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Cited by 91 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Action recognition is a relatively established task, where givenan input sequence of human motion, the goal is to predict its ac-tion category. This paper, on the other hand, considers a relativelynew problem, which could be thought of as an inverse of actionrecognition: given a prescribed action type, we aim to generateplausible human motion sequences in 3D. Importantly, the set ofgenerated motions are expected to maintain itsdiversityto be ableto explore the entire action-conditioned motion space; meanwhile,each sampled sequence faithfully resembles anaturalhuman bodyarticulation dynamics. Motivated by these objectives, we followthe physics law of human kinematics by adopting the Lie Algebratheory to represent thenaturalhuman motions; we also propose atemporal Variational Auto-Encoder (VAE) that encourages adiversesampling of the motion space. A new 3D human motion dataset, HumanAct12, is also constructed. Empirical experiments overthree distinct human motion datasets (including ours) demonstratethe effectiveness of our approach.

Key facts. Cited by 438 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 10; 2022: 48; 2023: 84; 2024: 105; 2025: 122; 2026: 69.

438 papers.

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  1. 2022Human Motion Diffusion Modelcited by 1,062
  2. 2022MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Modelcited by 768
  3. 2023T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representationscited by 577
  4. 2022Executing your Commands via Motion Diffusion in Latent Spacecited by 567
  5. 2023MotionGPT: Human Motion as a Foreign Languagecited by 521
  6. 2021Action-Conditioned 3D Human Motion Synthesis with Transformer VAEcited by 497
  7. 2022TEMOS: Generating diverse human motions from textual descriptionscited by 486
  8. 2022MotionCLIP: Exposing Human Motion Generation to CLIP Spacecited by 406
  9. 2023MoMask: Generative Masked Modeling of 3D Human Motionscited by 388
  10. 2022PhysDiff: Physics-Guided Human Motion Diffusion Modelcited by 365
  11. 2022TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Textscited by 357
  12. 2022EDGE: Editable Dance Generation From Musiccited by 284
38 more
  1. 2023ReMoDiffuse: Retrieval-Augmented Motion Diffusion Modelcited by 282
  2. 2021BABEL: Bodies, Action and Behavior with English Labelscited by 261
  3. 2023OmniControl: Control Any Joint at Any Time for Human Motion Generationcited by 233
  4. 2023Guided Motion Diffusion for Controllable Human Motion Synthesiscited by 221
  5. 2023Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Datasetcited by 220
  6. 2022MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesiscited by 218
  7. 2022FLAME: Free-form Language-based Motion Synthesis & Editingcited by 217
  8. 2023InterGen: Diffusion-based Multi-human Motion Generation under Complex Interactionscited by 205
  9. 2023TMR: Text-to-Motion Retrieval Using Contrastive 3D Human Motion Synthesiscited by 194
  10. 2022TEACH: Temporal Action Composition for 3D Humanscited by 173
  11. 2024MotionLCM: Real-time Controllable Motion Generation via Latent Consistency Modelcited by 164
  12. 2022HUMANISE: Language-conditioned Human Motion Generation in 3D Scenescited by 156
  13. 2023MotionGPT: Finetuned LLMs Are General-Purpose Motion Generatorscited by 145
  14. 2021GOAL: Generating 4D Whole-Body Motion for Hand-Object Graspingcited by 142
  15. 2023CG-HOI: Contact-Guided 3D Human-Object Interaction Generationcited by 137
  16. 2023MMM: Generative Masked Motion Modelcited by 129
  17. 2023State of the Art on Diffusion Models for Visual Computingcited by 126
  18. 2022IMos: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactionscited by 121
  19. 2023AttT2M: Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanismcited by 116
  20. 2024Motion Mamba: Efficient and Long Sequence Motion Generationcited by 111
  21. 2024Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wildcited by 109
  22. 2023Inter-X: Towards Versatile Human-Human Interaction Analysiscited by 98
  23. 2023Optimizing Diffusion Noise Can Serve As Universal Motion Priorscited by 97
  24. 2023Human Motion Generation: A Surveycited by 95
  25. 2023TLControl: Trajectory and Language Control for Human Motion Synthesiscited by 93
  26. 2022Towards Diverse and Natural Scene-aware 3D Human Motion Synthesiscited by 91
  27. 2023EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generationcited by 88
  28. 2024Multi-Track Timeline Control for Text-Driven 3D Human Motion Generationcited by 88
  29. 2022Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fieldscited by 85
  30. 2022BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Predictioncited by 82
  31. 2023HumanMAC: Masked Motion Completion for Human Motion Predictioncited by 81
  32. 2023Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Modelcited by 79
  33. 2024Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordancecited by 79
  34. 2022PoseGPT: Quantization-based 3D Human Motion Generation and Forecastingcited by 78
  35. 2024Rethinking Diffusion for Text-Driven Human Motion Generation: Redundant Representations, Evaluation, and Masked Autoregressioncited by 78
  36. 2022ActFormer: A GAN-based Transformer towards General Action-Conditioned 3D Human Motion Generationcited by 77
  37. 2023TM2D: Bimodality Driven 3D Dance Generation via Music-Text Integrationcited by 76
  38. 2023PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interactioncited by 72

50 most cited of 438 All 438 (JSON)