Datasets:
File size: 1,923 Bytes
21a1e3e 069e675 21a1e3e d769bdb 9f08f8a 069e675 9f08f8a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
task_categories:
- image-classification
- point-cloud-classification
- point-cloud-recognition
---
The datasets in this repository are used in the paper [Point-Cache: Test-time Dynamic and Hierarchical Cache for Robust and Generalizable Point Cloud Analysis](http://arxiv.org/abs/2503.12150).
### Datasets
1. The folder structure of used datasets should be organized as follows.
```sh
/path/to/Point-Cache
|----data # placed in the same level as `runners`, `scripts`, etc.
|----modelnet_c
|----sonn_c
|----obj_bg
|----obj_only
|----hardest
|----modelnet40
|----scanobjnn
|----omniobject3d
|----1024
|----4096
|----16384
|----objaverse_lvis
|----runners
|----scripts
...
```
2. You can find the download links of the above datasets from our **huggingface dataset repositories** as follows.
- [Link](https://huggingface.co/datasets/auniquesun/Point-PRC/tree/main/new-3ddg-benchmarks/xset/corruption) for `modelnet_c` and `sonn_c`
- [Link](https://huggingface.co/datasets/auniquesun/Point-PRC/tree/main/new-3ddg-benchmarks/xset/dg) for `omniobject3d`
- [Link](https://huggingface.co/datasets/auniquesun/Point-Cache/tree/main) for `modelnet40`, `scanobjnn`, and `objaverse_lvis`
3. If you find our paper and datasets are helpful for your project or research, please cite our work as follows.
```bibtex
@InProceedings{Sun_2025_CVPR,
author = {Sun, Hongyu and Ke, Qiuhong and Cheng, Ming and Wang, Yongcai and Li, Deying and Gou, Chenhui and Cai, Jianfei},
title = {Point-Cache: Test-time Dynamic and Hierarchical Cache for Robust and Generalizable Point Cloud Analysis},
booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
month = {June},
year = {2025},
pages = {1263-1275}
}
``` |