|
--- |
|
license: apache-2.0 |
|
task_categories: |
|
- image-to-3d |
|
language: |
|
- en |
|
tags: |
|
- 3d |
|
- images |
|
size_categories: |
|
- 1K - 10K |
|
--- |
|
|
|
# InstantSplat: Sparse-view SfM-free Gaussian Splatting in Seconds |
|
|
|
[[Project Page]](https://instantsplat.github.io/) | [[Arxiv]](https://arxiv.org/abs/2403.20309) | [[Video]](https://www.youtube.com/watch?v=fxf_ypd7eD8) | [[Code]](https://github.com/NVlabs/InstantSplat) | [[HF Demo]](https://huggingface.co/spaces/kairunwen/InstantSplat) |
|
|
|
|
|
## Overview |
|
This repository contains two large-scale datasets: [Tanks and Temples](https://dl.acm.org/doi/abs/10.1145/3072959.3073599) and [MVimgNet](https://openaccess.thecvf.com/content/CVPR2023/papers/Yu_MVImgNet_A_Large-Scale_Dataset_of_Multi-View_Images_CVPR_2023_paper.pdf). |
|
1. **Tanks and Temples**: This dataset includes five outdoor scenes and three indoor scenes, namely Barn, Family, Francis, Horse, Ignatius, Church, Ballroom, and Museum. |
|
2. **MVimgNet**: This dataset comprises seven outdoor scenes, covering a variety of scene types such as Car, SUV, Bicycle, Chair, Ladder, Bench, and Table. |
|
|
|
|
|
## Citation |
|
If you find this repository/work/dataset helpful in your research, please consider citing the paper and starring the [repo](https://github.com/NVlabs/InstantSplat) ⭐. |
|
``` |
|
@misc{fan2024instantsplat, |
|
title={InstantSplat: Unbounded Sparse-view Pose-free Gaussian Splatting in 40 Seconds}, |
|
author={Zhiwen Fan and Wenyan Cong and Kairun Wen and Kevin Wang and Jian Zhang and Xinghao Ding and Danfei Xu and Boris Ivanovic and Marco Pavone and Georgios Pavlakos and Zhangyang Wang and Yue Wang}, |
|
year={2024}, |
|
eprint={2403.20309}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CV} |
|
} |
|
``` |
