PhysGaia: A Physics-Aware Benchmark with Multi-Body Interactions for Dynamic Novel View Synthesis
Paper • 2506.02794 • Published
Mijeong Kim* · Gunhee Kim* · Jungyoon Choi · Wonjae Roh · Bohyung Han
{material_type}_{scene_name}.zip
│
├── render/ # Generated images (e.g., avatar renderings)
│ ├── train/ # Images for training
│ └── test/ # Images for evaluation
│
├── point_cloud.ply # COLMAP initialization (PatchMatch & downsampling)
├── camera_info_test.json # Monocular camera info for test
├── camera_info_train_mono.json # Monocular camera info for training
├── camera_info_train_multi.json # Multi-view camera info for training
│
├── {scene_name}.hipnc # Houdini source file (simulation or scene setup)
├── particles/ # Ground-truth trajectories
Please check each branch for integrated code for recent DyNVS methods.
@inproceedings{kim2026physgaia,
title={PhysGaia:Physics-Aware Benchmark with Multi-Body Interactions for Dynamic Novel View Synthesis},
author={Kim, Mijeong and Kim, Gunhee and Choi, Jungyoon and Roh, Wonjae and Han, Bohyung},
booktitle={CVPR},
year={2026}
}
We welcome contributions to expand the dataset (additional modality for new downstream tasks, , implementation for other models, etc.) Reach out via opening an issue/discussion in the repo.
This project is released under the Creative Commons Attribution-NonCommercial 4.0 license. ✅ Free to use, share, and adapt for non-commercial research