Official implementation of Adaptive Pyramid Context Network for Semantic Segmentation (Paper).
🔥🔥 APCNet is on MMsegmentation. 🔥🔥
@InProceedings{He_2019_CVPR,
author = {He, Junjun and Deng, Zhongying and Zhou, Lei and Wang, Yali and Qiao, Yu},
title = {Adaptive Pyramid Context Network for Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| APCNet | R-50-D8 | 512x1024 | 40000 | 7.7 | 3.57 | 78.02 | 79.26 | config | model | log |
| APCNet | R-101-D8 | 512x1024 | 40000 | 11.2 | 2.15 | 79.08 | 80.34 | config | model | log |
| APCNet | R-50-D8 | 769x769 | 40000 | 8.7 | 1.52 | 77.89 | 79.75 | config | model | log |
| APCNet | R-101-D8 | 769x769 | 40000 | 12.7 | 1.03 | 77.96 | 79.24 | config | model | log |
| APCNet | R-50-D8 | 512x1024 | 80000 | - | - | 78.96 | 79.94 | config | model | log |
| APCNet | R-101-D8 | 512x1024 | 80000 | - | - | 79.64 | 80.61 | config | model | log |
| APCNet | R-50-D8 | 769x769 | 80000 | - | - | 78.79 | 80.35 | config | model | log |
| APCNet | R-101-D8 | 769x769 | 80000 | - | - | 78.45 | 79.91 | config | model | log |
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| APCNet | R-50-D8 | 512x512 | 80000 | 10.1 | 19.61 | 42.20 | 43.30 | config | model | log |
| APCNet | R-101-D8 | 512x512 | 80000 | 13.6 | 13.10 | 45.54 | 46.65 | config | model | log |
| APCNet | R-50-D8 | 512x512 | 160000 | - | - | 43.40 | 43.94 | config | model | log |
| APCNet | R-101-D8 | 512x512 | 160000 | - | - | 45.41 | 46.63 | config | model | log |