---
license: mit
task_categories:
- image-to-3d
---
# EKS Dataset
This repository contains the data and assets used in the paper [Affine-Equivariant Kernel Space Encoding for NeRF Editing](https://huggingface.co/papers/2508.02831), which introduces a hybrid model for interactive editing of Neural Radiance Fields.
[Project page](https://mikolajzielinski.github.io/eks.github.io/) | [Code](https://github.com/MikolajZielinski/eks)
# Dataset content
In the following folders you can find:
- `blender` - our animations with scripts used to generate them
- `configs` - configuration files used during the experimetns shown in our paper
- `data` - contains NeRF Synthetic + Our Assets wit appriopriate `sparse_pc.ply` used for initialization of the system
- `permuto_SDF_models` - meshes generated with [PermutoSDF](https://radualexandru.github.io/permuto_sdf/) that we have used for driving the Gaussians
Dataset lacks the data for Mip-NeRF 360 dataset which can be downloaded from [here](https://jonbarron.info/mipnerf360/) and also fox which can be found [here](https://github.com/NVlabs/instant-ngp).
Additionally Mip-NeRF 360 shoud be processed with:
``` bash
# Do this for every dataset in the folder
cd
ns-process-data images --data . --output-dir . --skip-colmap --skip-image-processin --colmap-model-path sparse/0
```
# Bugs in nerfstudio 1.1.4
There were a few bugs in nerfstudio we needed to fix in order to train on Mip-NeRF 360 dataset:
File: nerfstudio/exporter/exporter_utils.py
``` python
# Lines 166-172
# Change from:
if crop_obb is not None:
mask = crop_obb.within(point)
point = point[mask]
rgb = rgb[mask]
view_direction = view_direction[mask]
if normal is not None:
normal = normal[mask]
# To:
if crop_obb is not None:
mask = crop_obb.within(point)
point = point[mask]
rgb = rgb[mask]
view_direction = view_direction[mask]
if normal is not None:
normal = normal[mask]
```
File: nerfstudio/model_components/ray_generators.py
``` python
# Lines 49-50
# Change from:
y = ray_indices[:, 1] # row indices
x = ray_indices[:, 2] # col indices
# To:
y = torch.clamp(ray_indices[:, 1], 0, self.image_coords.shape[0] - 1) # row indices
x = torch.clamp(ray_indices[:, 2], 0, self.image_coords.shape[1] - 1) # col indices
```
File: nerfstudio/utils/eval_utils.py
``` python
# Line 62
# Change from:
loaded_state = torch.load(load_path, map_location="cpu")
# To:
loaded_state = torch.load(load_path, map_location="cpu", weights_only=False)
```
## 📄 Citation
If you use our data, please cite:
```bibtex
@misc{zielinski2025eks,
title = {Affine-Equivariant Kernel Space Encoding for NeRF Editing},
author = {Miko\l{}aj Zieli\'{n}ski and Krzysztof Byrski and Tomasz Szczepanik and Dominik Belter and Przemys\l{}aw Spurek},
year = {2025},
eprint = {2508.02831},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2508.02831}
}
```