Training free panorama generation with inpainting via equirectangular mapping

This code implements a traning-free 360 panorama generation pipeline via equirectangular projection and inpainting based on the 2025 Meta paper "A Recipe for Generating 3D Worlds From a Single Image".

Method Overview

This implementation follows the panorama generation method described in the paper. The approach uses a progressive inpainting strategy with equirectangular projection:

Panorama Synthesis Process

1. Equirectangular Projection: The input perspective image is first embedded into an equirectangular panorama by converting pixel coordinates to spherical coordinates (θ, φ) and then to equirectangular coordinates.

2. Progressive Inpainting: The method implements an "Anchored" synthesis strategy where:

   • The input image is duplicated to the backside of the panorama to anchor the synthesis
   • Separate prompts are generated for sky and ground regions using a vision-language model
   • The synthesis begins with sky and ground generation to maximize global context
   • The backside anchor is then removed and remaining regions are generated by rendering and outpainting perspective images
   • Multiple overlapping perspective views are rendered (8 images with 85° FoV for middle region, 4 images each with 120° FoV for top/bottom)
   

   Figure: Anchored synthesis strategy showing the input image (center) duplicated to the backside, with numbered regions (1-4) indicating the progressive inpainting order.

3. Inpainting Network: Uses a ControlNet-based inpainting model conditioned on masked input images. The inpainting network is based on FLUX-Controlnet-Inpainting.

4. Refinement: Optionally, a partial denoising process is applied to improve image quality and ensure smooth transitions between inpainted regions.

For more details, refer to the original paper: "A Recipe for Generating 3D Worlds From a Single Image" (ICCV 2025).

Example Outputs

Prompt : "a market square in the 1800s"

Prompt : "a modern japanese garden with a pond and a waterfall"

Install

conda create -n pano_gen python=3.10
conda activate pano_gen
pip install -r requirements.txt

Run the Code

python world.py --scene_prompt "a modern japanese garden with a pond and a waterfall" --scene_prompt_sides "a modern japanese garden " --sky_prompt "a clear blue sky"

The output is then stored in imgs/ folder as pano.png

Due to consecutive creation of multiple images to fill the the equirectangular 360 layout the generation will take several minutes (multiple inference runs of the Flux-Dev Inpainting ControlNet model).

--scene_prompt : prompt for the middle center image generation 
--scene_prompt_sides : prompt for the sides of the image => should describe general scene layout, but can be less descriptive than scene_prompt
--sky_prompt : prompt for the sky image generation 
--debug : optional mode that stores all inpainting masks, etc.

If you find this code useful, please don't forget to cite the original paper and the codebase :

@misc{perauer2026panoramageninpaint,
  author = {Perauer, Cedric},
  title = {PanoramaGenInpaint: Panorama Generation with Inpainting Models based on "A Recipe for Generating 3D Worlds From a Single Image"},
  year = {2026},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/Cedric-Perauer/PanoramaGenInpaint}}
}

@misc{schwarz2025recipegenerating3dworlds,
      title={A Recipe for Generating 3D Worlds From a Single Image}, 
      author={Katja Schwarz and Denys Rozumnyi and Samuel Rota Bulò and Lorenzo Porzi and Peter Kontschieder},
      year={2025},
      eprint={2503.16611},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2503.16611}, 
}