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DATASETS.md

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Datasets

For view synthesis experiments with Gaussian splatting, we mainly use RealEstate10K and DL3DV datasets. We provide the data processing scripts to convert the original datasets to pytorch chunk files which can be directly loaded with this codebase.

Expected folder structure:

├── datasets
│   ├── re10k
│   ├── ├── train
│   ├── ├── ├── 000000.torch
│   ├── ├── ├── ...
│   ├── ├── ├── index.json
│   ├── ├── test
│   ├── ├── ├── 000000.torch
│   ├── ├── ├── ...
│   ├── ├── ├── index.json
│   ├── dl3dv
│   ├── ├── train
│   ├── ├── ├── 000000.torch
│   ├── ├── ├── ...
│   ├── ├── ├── index.json
│   ├── ├── test
│   ├── ├── ├── 000000.torch
│   ├── ├── ├── ...
│   ├── ├── ├── index.json

By default, we assume the datasets are placed in datasets/re10k and datasets/dl3dv. Otherwise you will need to specify your dataset path with dataset.roots=[YOUR_DATASET_PATH] in the running script.

We also provide instructions to convert additional datasets to the desired format.

RealEstate10K

For experiments on RealEstate10K, we primarily follow pixelSplat and MVSplat to train and evaluate on 256x256 resolution.

Please refer to here for acquiring the processed 360p dataset (360x640 resolution).

If you would like to train and evaluate on the high-resolution RealEstate10K dataset, you will need to download the 720p (720x1280) version. Please refer to here for the downloading script. Note that the script by default downloads the 360p videos, you will need to modify the360p to 720p in this line of code to download the 720p videos.

After downloading the 720p dataset, you can use the scripts here to convert the dataset to the desired format in this codebase.

DL3DV

For experiments on DL3DV, we mainly train and evaluate on 256x448 resolution.

For the test set, we use the DL3DV-Benchmark split, which contains 140 scenes for evaluation. You can first use the script src/scripts/convert_dl3dv_test.py to convert the test set, and then run src/scripts/generate_dl3dv_index.py to generate the index.json file for the test set.

For the training set, we use the DL3DV-480p dataset (270x480 resolution), where the 140 scenes in the test set are excluded during processing the training set. After downloading the DL3DV-480p dataset, You can first use the script src/scripts/convert_dl3dv_train.py to convert the training set, and then run src/scripts/generate_dl3dv_index.py to generate the index.json file for the training set.

Please note that you will need to update the dataset paths in the aforementioned processing scripts.

If you would like to train and evaluate on the high-resolution DL3DV dataset, you will need to download the DL3DV-960P version (540x960 resolution). Simply follow the same procedure for data processing (use the images_4 folder instead of images_8).

Please follow the DL3DV license if you use this dataset in your project and kindly reference the DL3DV paper.

Additional Datasets

If you would like to train and/or evaluate on additional datasets, just modify the data processing scripts to convert the dataset format. Kindly note the camera conventions used in this codebase.