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myst

Myst is a combination of Stable Diffusion and VGGT (Visual Geometry Grounded Transformer)/DepthAnything/Metric3D to create worlds that are 3D aware and go beyond outpainting.

Simply, Myst lets you start with a text prompt, "an image of a kitchen", generates a 2D image from it using diffusion, lifts the 2D image to 3D, and then lets you navigate around the scene. As you rotate/move to reveal unexplored parts of the scene, you can run additional diffusion steps and new images are generated and then combined into a single, coherent, 3D scene.

Update: We've replaced Dust3r/Mast3r with VGGT, the CVPR 2025 Best Paper Award winner, for faster and more accurate 3D reconstruction.

We can create infinite 3D scenes, for use as a potential dataset. We can manually create these worlds, or do it automatically.

Architecture: Showing how we created these worlds.

Architecture

Real-time Generation: A real-time recording of me creating a kitchen scene using Stable Diffusion and Dust3r.

Real-time generation

Automatic Dataset: Showing a few automatic datasets.

Automatic Dataset


A Few Scenes

LOTS of bay windows..
Screencast 10
What happens in a long hallway?
Screencast 11
Monastery tunnels
Screencast 12
Full 360 beach views
Screencast 01
Kitchen meets a fireplace
Screencast 02
Nice wood oak paneling
Screencast 03
Super mario kitchen-land
Screencast 04
Severance hallway?
Screencast 05
More beach and ocean views
Screencast 06
Spacious bedroom kitchens
Screencast 07
Fireplace bedroom kitchens
Screencast 08
Interesting ceilings
Screencast 09

Synthetic Dataset

Urban spook
Screencast 10
Mountains and ducks
Screencast 11
Marble, books, plants
Screencast 01
Buddha, cape town, aerial
Screencast 02
Venice and ruins
Screencast 03
More kitchens
Screencast 03

Installation

# Clone the repository
git clone https://github.com/your-repo/myst.git
cd myst

# Run setup (installs all dependencies and downloads model checkpoints)
chmod +x setup_env.sh
./setup_env.sh

Prerequisites: Python 3.12+, CUDA 12.x+, uv package manager

Run

Default mode now uses VGGT for 3D reconstruction:

python run.py --depth vggt

You can also use other depth estimation methods:

  • --depth vggt (default): VGGT - fastest and most accurate (CVPR 2025 Best Paper)
  • --depth metric: Metric3D
  • --depth da: Depth Anything
  • --depth dust: Dust3r (requires ./setup_env.sh --with-dust3r)
  • --depth mast3r: Mast3r (requires ./setup_env.sh --with-dust3r)

Command Line Options

python run.py [OPTIONS]

Options:
  --headless              Don't show GUI
  --depth DEPTH           vggt / metric / da / dust
  --renderer RENDERER     raster / py3d
  --prompt PROMPT         me / doors / auto / combo / default
  --control CONTROL       me / doors / auto
  --intrinsics INTRINSICS dummy / pf
  --image IMAGE           gen / path
  --model MODEL           sd2 / if

Examples

# Interactive mode with VGGT
python run.py --depth vggt --prompt auto --control auto

# Headless mode for dataset generation
python run.py --headless --depth vggt --prompt auto --control auto

# Use specific image as starting point
python run.py --image path/to/your/image.jpg --depth vggt

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