Infinigen is a procedural generation system that creates infinite photorealistic worlds for computer vision and simulation applications.
The tool addresses the challenge of generating large-scale, diverse, and annotated synthetic datasets by using procedural generation to create photorealistic environments and objects. Rather than manually modeling scenes, Infinigen procedurally generates natural landscapes, indoor rooms, and articulated objects with full control over their properties. The system produces not only RGB images but also dense annotations including depth maps, surface normals, and instance segmentation, making the generated data immediately useful for training vision models.
Infinigen suits projects requiring large quantities of synthetic training data where manual scene creation would be prohibitively expensive. It is particularly valuable for computer vision research, simulation environments, and robotics applications that need diverse, annotated datasets. The tool offers multiple specialized tracks: a nature-focused version for outdoor scenes and landscapes, an indoors version for room-scale environments with furniture and objects, and an articulated version for generating objects suitable for physics simulation. Teams should choose this tool when they need scalable dataset generation with fine-grained control over scene composition and automatic annotation rather than hand-crafted or limited synthetic datasets.
The project maintains multiple stable branches alongside a main development line, indicating active parallel development across different specializations. Development activity shows ongoing refinement of core generation capabilities, with documentation and getting-started guides kept current across the different tracks. The codebase demonstrates sustained engineering effort to support export pipelines to external simulators and to maintain compatibility across the nature, indoors, and articulated variants.
