README.md

HV-plane reconstruction from a single 360 image

Code for our paper in CVPR 2021: Indoor Panorama Planar 3D Reconstruction via Divide and Conquer (paper, video)

Pretrained models

Download our pretrained models from google drive or dropbox.

Inference on 360 datas

1. Please resize your images into 512 x 1024.
2. Follow the preprocessing step here to ensure Mahattan alignment of your 360 images.
3. Run our inference script. Examples:

python inference.py --pth ckpt/mp3d.pth --glob static/demo.png --outdir static/mp3d_model_results

To run on a batch of images, you can use --glob "AWESOME_360_IMAGES_DIR/*png"

Visualize the results

Here is the visulization example on a held-out data:

python vis_planes.py --img static/demo.png --h_planes static/mp3d_model_results/demo.h_planes.exr --v_planes static/mp3d_model_results/demo.v_planes.exr --mesh

To always visualize all the planes, add --mesh_show_back_face.

Citation

@inproceedings{SunHWSC21,
  author    = {Cheng Sun and
               Chi{-}Wei Hsiao and
               Ning{-}Hsu Wang and
               Min Sun and
               Hwann{-}Tzong Chen},
  title     = {Indoor Panorama Planar 3D Reconstruction via Divide and Conquer},
  booktitle = {CVPR},
  year      = {2021},
}