luciddreamer-cvlab/LucidDreamer

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1528 stars · 111 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LucidDreamer is the official implementation of a research method that generates 3D Gaussian Splatting scenes from text prompts, published in IEEE TVCG 2025 (Best Paper Runner-Up). It combines diffusion-based image generation with depth estimation and Gaussian splatting to create domain-free 3D scenes.

Use cases

• generate 3d scenes from text prompts
• create gaussian splatting scenes without domain-specific training
• text to 3d scene generation for research
• produce 3d environments for visualization papers
• generate novel 3d worlds from a description

When to choose

• you need text-to-3D scene generation with Gaussian splatting
• you are reproducing or building on the LucidDreamer paper
• you want a research-grade pipeline combining diffusion models and 3DGS

When to avoid

• you need a commercially licensed tool (CC BY-NC-SA 4.0)
• you need production-ready 3D content creation software
• you cannot run CUDA/GPU workloads

Facets

library · maturity active

machine-learning deep-learning image-processing graphics simulation artificial-intelligence computer-vision graphics deep-learning windows python 3d-gaussian-splatting text-to-3d scene-generation diffusion-models depth-estimation research-code non-commercial-license linux gpu

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