mipal/iPhone360-4dgs360

iPhone360 Dataset - 4dgs360 preprocessed version

iPhone360 is a benchmark dataset for 360° reconstruction of dynamic objects from monocular video, introduced in the paper:

4DGS360: 360° Gaussian Reconstruction of Dynamic Objects from a Single Video Jae Won Jang, Yeonjin Chang, Wonsik Shin, Juhwan Cho, Nojun Kwak Project Page · arXiv

Dataset Description

iPhone360 features real-world dynamic scenes captured with an iPhone, where test cameras are positioned at significantly different angles from training views. This enables evaluation of 360° reconstruction capabilities that existing datasets cannot provide.

Dataset Versions

This dataset is distributed in two versions:

• —`iPhone360-4dgs360` (this folder) — includes all preprocessing outputs required to reproduce 4DGS360 training and evaluation end-to-end (2D/3D tracks, track-anything masks, refined depth/tracks from AnchorTAPIP3D, cached scene-normalization tensors, etc.). Large footprint.
• —[`iPhone360`](https://huggingface.co/datasets/mipal/iPhone360) — the same RGB/depth/mask/camera/points/splits data, with the 4DGS360-specific intermediate preprocessing outputs above excluded. Much smaller download.

If you're quickly adapting iPhone360 to a new paper/method, we recommend starting with `iPhone360 version` and evaluating on it first, rather than downloading the full iPhone360-4dgs360.

Scenes

Data Structure

Each scene contains:

• —rgb/ — RGB frames
• —depth/ — Depth maps
• —masks/ — Object masks
• —camera/ — Camera parameters
• —splits/ — Train/test split definitions
• —points.npy — Initial point cloud
• —dataset.json / scene.json / metadata.json — Scene metadata
• —flow3d_preprocessed/ — Preprocessed optical flow data
• —video_depth_anything/ — Video depth estimates

Citation

If you use this dataset, please cite:

@article{jang2025_4dgs360,
  title     = {4DGS360: 360° Gaussian Reconstruction of Dynamic Objects from a Single Video},
  author    = {Jang, Jae Won and Chang, Yeonjin and Shin, Wonsik and Cho, Juhwan and Kwak, Nojun},
  journal   = {arXiv preprint arXiv:2603.21618},
  year      = {2025},
  url       = {https://arxiv.org/abs/2603.21618}
}

Download and extraction

The complete preprocessed dataset is distributed as 21 independent tar archives in the six scene folders at the repository root. Download every archive for each scene you need. Each archive preserves paths starting with its scene name; extract all archives into the same destination directory to restore the layout described above. These are independent tar files, not split parts of a single tar.

hf download mipal/iPhone360-4dgs360 --repo-type dataset --local-dir iphone360-download
cd iphone360-download
shasum -a 256 -c SHA256SUMS
mkdir -p ../iphone360-extracted
for archive in block2/*.tar goat/*.tar jacket/*.tar jelly/*.tar pull-up/*.tar walk-around/*.tar; do
  tar -xf "$archive" -C ../iphone360-extracted || exit 1
done

manifests/ contains each scene's original file paths, byte sizes, and modification timestamps. SHA256SUMS contains checksums of the tar archives.