Building the foundations of interactive worlds that are persistent, multi-agent, and universally authorable — driven by our research in generative 3D and world models.
Open-source 3D Gaussian generator. Unmatched quality, controllable budget, minimal dependency.
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A versatile open-source model for converting any image to a high-quality 3D mesh.
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Fast textured mesh generation. No GPU required. Built with Stability.AI.
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Learn MoreBuilt on native brick tokenization and backed by our 55,000-model LegoVerse dataset, LegoACE is an autoregressive engine that generates expressive LEGO assemblies from text or normal maps.
TripoSplat introduces Density-Sampled Gaussians (DeG) for fully adaptive, grid-free 3D generation. We achieve differentiable densification by parameterizing primitive centers as samples from a learnable spatial density, optimized directly via a novel render-loss gradient. To model these unstructured sets, our VecSeq diffusion framework resolves permutation ambiguity by anchoring latents to a deterministic 3D Sobol sequence. TripoSplat achieves state-of-the-art single-image-to-3D generation while uniquely enabling variable-resolution decoding from a single compact latent code.
By jointly representing shape, skeleton, and skinning as mutually consistent S³ Fields, AniGen produces animation-ready 3D assets from a single image, substantially outperforming prior methods in rig validity.
We pursue first-principles research in 3D, from spatial reasoning and neural graphics to interactive world models. Our work has been consistently recognized at top venues such as SIGGRAPH, CVPR, NeurIPS, and ICCV, and we have open-sourced 30+ projects to advance the broader community.
We offer competitive compensation, ownership of core technical directions, dedicated large-scale compute, and a focused research culture built for long-term, high-impact work.
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