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[ECCV-W 2024] Code for Sp2360: Sparse-view 360° Scene Reconstruction using Cascaded 2D Diffusion Priors

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Sp2360: Sparse-view 360° Scene Reconstruction using Cascaded 2D Diffusion Priors

Soumava Paul · Christopher Wewer · Bernt Schiele · Jan Eric Lenssen

Method

Data Creation

Dataset

Our experiments are based on the MipNeRF360 benchmark available here and here. Download and put the dataset under data/360_v2 in the root directory.

Implementation

Currently the repository only has functionalities for our view selection algorithm outlined in A.1. The full implementation of the method will be released soon.

To sample an M-view subset from a given multiview set, run:

python -m utils.view_splits --source_path data/360_v2/<scene>/<scene>_train --test_cams data/360_v2/<scene>/<scene>_test --num_eval_views M  --eval

where <scene> ∈ {bicycle, garden, flowers, stump, treehill, room, counter, kitchen, bonsai}.

🎓 Cite

If this code was helpful for your research, consider citing:

@article{paul2024sp2360,
          title={Sp2360: Sparse-view 360 Scene Reconstruction using Cascaded 2D Diffusion Priors},
          author={Paul, Soumava and Wewer, Christopher and Schiele, Bernt and Lenssen, Jan Eric},
          journal={arXiv preprint arXiv:2405.16517},
          year={2024}
}        

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[ECCV-W 2024] Code for Sp2360: Sparse-view 360° Scene Reconstruction using Cascaded 2D Diffusion Priors

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