--- 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)

EKS Teaser Image

# 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} } ```