| --- |
| license: mit |
| tags: |
| - nerf |
| - neural-fields |
| - permutation-symmetry |
| - model-merging |
| --- |
| |
| # Trained NeRF pairs for "Progressive Permutation Alignment with Temperature-Controlled Spectral Sharpening" (ACCV 2026) |
|
|
| Code: https://github.com/yuzu0308/progressive-permutation-alignment |
|
|
| 16 vanilla NeRFs (nerfstudio 1.1.5 `vanilla-nerf`, 1M iterations) trained on the 8 scenes of NeRF Synthetic |
| with two random seeds each. These are the model pairs used for the interpolation (linear mode connectivity) |
| experiments of the paper. |
|
|
| | File | Content | |
| |---|---| |
| | `<scene>/model_a.pth` | state dict of the model trained with seed 42 (only the `field_coarse.*` / `field_fine.*` entries) | |
| | `<scene>/model_b.pth` | same for seed 100 | |
| | `<scene>/ref_perms_cpu.pt` | permutations found by the original research code (`pa`: Ours w/o Ref., `pa_wm`: Ours), used by the regression test | |
|
|
| Scenes: lego, chair, ficus, hotdog, mic, ship, materials, drums. |
|
|
| ```bash |
| pip install huggingface_hub |
| python scripts/download_weights.py # from the code repository |
| ``` |
|
|
| ```python |
| from ppa.nerf import load_state_dict |
| a = load_state_dict("weights/lego/model_a.pth") |
| ``` |
|
|
| The LPIPS network weights that nerfstudio stores in its checkpoints are not included; they are not needed |
| for alignment or rendering. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{horioka2026progressive, |
| title = {Progressive Permutation Alignment with Temperature-Controlled Spectral Sharpening}, |
| author = {Horioka, Yuta and Chiba, Naoya and Uranishi, Yuki}, |
| booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV)}, |
| year = {2026} |
| } |
| ``` |
|
|
