scintigimcki/DynScenesExtrap

NVIDIA Dynamic Scenes Dataset - Extrapolation Type

This dataset is proposed by Novel View Synthesis. NVFi selected skating and truck scenes from it, and rearrange the scenes to enable future extrapolation evaluation, and it's used by FreeGave and TRACE.

Structure

The structure of the dataset is as:

Dynamic Scenes
| - data
| | - Skating: data for Skating scene
| | | - train: serves as training data
| | | - val: used for evaluating novel view interpolation
| | | - test: used for evaluating future extrapolation
| | | - transforms_train.json: camera poses and other meta informations for training set
| | | - transforms_val.json: camera poses and other meta informations for novel view interpolation task
| | | - transforms_test.json: camera poses and other meta informations for future extrapolation task
| | | - points3d.ply: randomly initialized points for 3D Gaussians
| | - Truck: data for Truck scene

Citation

If you find this dataset helpful, please consider cite:

@article{li2023nvfi,
  title={NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videos}, 
  author={Jinxi Li and Ziyang Song and Bo Yang},
  year={2023},
  journal={NeurIPS}
}

Also please cite the original data contributors:

@article{yoon2020dynamic,
title={Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Camera},
author={Yoon, Jae Shin and Kim, Kihwan and Gallo, Orazio and Park, Hyun Soo and Kautz, Jan},
booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month={June},
year={2020}
}
}