GameFactory: Creating New Games with Generative Interactive Videos
On the map: World models → Video-generation world models and simulators
Abstract (arXiv)
Generative videos have the potential to revolutionize game development by autonomously creating new content. In this paper, we present GameFactory, a framework for action-controlled scene-generalizable game video generation. We first address the fundamental challenge of action controllability by introducing GF-Minecraft, an action-annotated game video dataset without human bias, and developing an action control module that enables precise control over both keyboard and mouse inputs. We further extend to support autoregressive generation for unlimited-length interactive videos. More importantly, GameFactory tackles the critical challenge of scene-generalizable action control, which most existing methods fail to address. To enable the creation of entirely new and diverse games beyond fixed styles and scenes, we leverage the open-domain generative priors from pre-trained video diffusion models. To bridge the domain gap between open-domain priors and small-scale game datasets, we propose a multi-phase training strategy with a domain adapter that decouples game style learning from action control. This decoupling ensures that action control learning is no longer bound to specific game styles, thereby achieving scene-generalizable action control. Experimental results demonstrate that GameFactory effectively generates open-domain action-controllable game videos, representing a significant step forward in AI-driven game generation.
Key facts. Cited by 124 papers in the map (data through 7 Oct 2026). Placed in Video-generation world models and simulators, one of 11 directions in World models. Builds on 46 of its 53 references that are in the map. First posted on arXiv 14 Jan 2025.
Builds on
46 of 53 references.
Closest ancestors · 12
Same direction, newest first
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- 2021Learning Transferable Visual Models From Natural Language Supervision26 Feb
- 2020Score-Based Generative Modeling through Stochastic Differential Equations26 Nov
- 2020Denoising Diffusion Probabilistic Models19 Jun
Other references · 34
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- 2024Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motioncited by 167
- 2021DriveGAN: Towards a Controllable High-Quality Neural Simulationcited by 125
- 2023Compositional Foundation Models for Hierarchical Planningcited by 92
- 2020Learning to Simulate Dynamic Environments with GameGANcited by 86
- 2024Video as the New Language for Real-World Decision Makingcited by 86
- 2024The Matrix: Infinite-Horizon World Generation with Real-Time Moving Controlcited by 79
- 2023MP5: A Multi-modal Open-ended Embodied System in Minecraft via Active Perceptioncited by 67
- 2021Playable Video Generationcited by 63
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- 2024Playable Game Generationcited by 26
- 2023Promptable Game Models: Text-Guided Game Simulation via Masked Diffusion Modelscited by 22
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Citing papers per year: 2025: 57; 2026: 67.
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