| Corruption | mIoU pts | mIoU vox |
|---|---|---|
| Clean | 26.84 | 52.06 |
| Cam Crash | 13.65 | 27.39 |
| Frame Lost | 11.91 | 22.85 |
| Color Quant | 21.49 | 38.16 |
| Motion Blur | 20.79 | 38.64 |
| Brightness | 25.76 | 49.00 |
| Low Light | 19.78 | 37.38 |
| Fog | 24.78 | 46.69 |
| Snow | 9.49 | 19.39 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 18.76 | 37.49 | | Moderate | 9.19 | 19.88 | | Hard | 13.01 | 24.82 | | Average | 13.65 | 27.39 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 19.55 | 37.53 | | Moderate | 10.51 | 20.13 | | Hard | 5.69 | 10.89 | | Average | 11.91 | 22.85 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 26.30 | 49.76 | | Moderate | 23.36 | 40.73 | | Hard | 14.83 | 23.99 | | Average | 21.49 | 38.16 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 25.70 | 48.04 | | Moderate | 20.03 | 36.77 | | Hard | 16.66 | 31.13 | | Average | 20.79 | 38.64 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 26.48 | 51.17 | | Moderate | 25.89 | 49.34 | | Hard | 24.91 | 46.51 | | Average | 25.76 | 49.00 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 23.44 | 44.20 | | Moderate | 20.39 | 38.31 | | Hard | 15.53 | 29.65 | | Average | 19.78 | 37.38 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 25.30 | 48.04 | | Moderate | 24.92 | 47.10 | | Hard | 24.12 | 44.95 | | Average | 24.78 | 46.69 |
| Severity | mIoU pts | mIoU vox | | :----------: | :-----: | | | | Easy | 14.50 | 28.52 | | Moderate | 7.34 | 15.51 | | Hard | 6.64 | 14.16 | | Average | 9.49 | 19.39 |
@inproceedings{huang2023tri,
title={Tri-perspective view for vision-based 3d semantic occupancy prediction},
author={Huang, Yuanhui and Zheng, Wenzhao and Zhang, Yunpeng and Zhou, Jie and Lu, Jiwen},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={9223--9232},
year={2023}
}