Text2Action: Generative Adversarial Synthesis from Language to Action
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Cited by 25 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
In this paper, we propose a generative model which learns the relationship between language and human action in order to generate a human action sequence given a sentence describing human behavior. The proposed generative model is a generative adversarial network (GAN), which is based on the sequence to sequence (SEQ2SEQ) model. Using the proposed generative network, we can synthesize various actions for a robot or a virtual agent using a text encoder recurrent neural network (RNN) and an action decoder RNN. The proposed generative network is trained from 29,770 pairs of actions and sentence annotations extracted from MSR-Video-to-Text (MSR-VTT), a large-scale video dataset. We demonstrate that the network can generate human-like actions which can be transferred to a Baxter robot, such that the robot performs an action based on a provided sentence. Results show that the proposed generative network correctly models the relationship between language and action and can generate a diverse set of actions from the same sentence.
Key facts. Cited by 106 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Oct 2017.
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Citing papers per year: 2021: 6; 2022: 16; 2023: 22; 2024: 32; 2025: 19; 2026: 11.
106 papers.
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- 2023T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representationscited by 588
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- 2021Action-Conditioned 3D Human Motion Synthesis with Transformer VAEcited by 501
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50 most cited of 106 All 106 (JSON)
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38 more
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50 newest of 106 All 106 (JSON)
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- 2024Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordancecited by 80
- 2023Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Modelcited by 79
- 2024Flexible Motion In-betweening with Diffusion Modelscited by 71
- 2023Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphscited by 45
- 2024HanDiffuser: Text-to-Image Generation With Realistic Hand Appearancescited by 42
- 2024M2D2M: Multi-Motion Generation from Text with Discrete Diffusion Modelscited by 24
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12 most cited of 24 All 24 (JSON)
- 2026DC-Motion: Decoupling Structure and Details via Discrete-Continuous Tokens for Human Motion Generation28 May 2026
- 2026ECHO: Edge-Cloud Humanoid Orchestration for Language-to-Motion Control17 Mar 2026
- 2025FlowMotion: Target-Predictive Conditional Flow Matching for Jitter-Reduced Text-Driven Human Motion Generation2 Apr 2025
- 2025Biomechanics-Guided Residual Approach to Generalizable Human Motion Generation and Estimation8 Mar 2025
- 2024LS-GAN: Human Motion Synthesis with Latent-space GANs30 Dec 2024
- 2024Two-in-One: Unified Multi-Person Interactive Motion Generation by Latent Diffusion Transformer21 Dec 2024
- 2024Towards motion from video diffusion models19 Nov 2024
- 2024Pay Attention and Move Better: Harnessing Attention for Interactive Motion Generation and Training-free Editing24 Oct 2024
- 2024Text-driven Human Motion Generation with Motion Masked Diffusion Model29 Sep 2024
- 2024M2D2M: Multi-Motion Generation from Text with Discrete Diffusion Models19 Jul 2024
- 2024NL2Contact: Natural Language Guided 3D Hand-Object Contact Modeling with Diffusion Model17 Jul 2024
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12 newest of 24 All 24 (JSON)
- 2023T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representationscited by 588
- 2021Action-Conditioned 3D Human Motion Synthesis with Transformer VAEcited by 501
- 2022TEMOS: Generating diverse human motions from textual descriptionscited by 492
- 2023Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Datasetcited by 227
- 2021Synthesis of Compositional Animations from Textual Descriptionscited by 178
- 2022TEACH: Temporal Action Composition for 3D Humanscited by 176
- 2022IMos: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactionscited by 124
- 2023AttT2M: Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanismcited by 117
- 2023HumanTOMATO: Text-aligned Whole-body Motion Generationcited by 104
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- 2026ParTY: Part-Guidance for Expressive Text-to-Motion Synthesis10 Mar 2026
- 2026ZeroWBC: Learning Natural Whole-Body Humanoid Interaction from Human Egocentric Data10 Mar 2026
- 2026U-Mind: A Unified Framework for Real-Time Multimodal Interaction with Audiovisual Generation27 Feb 2026
- 2026A Self-Supervised Approach on Motion Calibration for Enhancing Physical Plausibility in Text-to-Motion20 Feb 2026
- 2026Language-Guided Transformer Tokenizer for Human Motion Generation9 Feb 2026
- 2026CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos15 Jan 2026
- 2025UniAct: Unified Motion Generation and Action Streaming for Humanoid Robots30 Dec 2025
- 2025Robust Motion Generation using Part-level Reliable Data from Videos14 Dec 2025
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