[ALGORITHM]
@inproceedings{sandler2018mobilenetv2,
title={Mobilenetv2: Inverted residuals and linear bottlenecks},
author={Sandler, Mark and Howard, Andrew and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={4510--4520},
year={2018}
}| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | download |
|---|---|---|---|---|---|---|---|---|
| FCN | M-V2-D8 | 512x1024 | 80000 | 3.4 | 14.2 | 61.54 | - | model | log |
| PSPNet | M-V2-D8 | 512x1024 | 80000 | 3.6 | 11.2 | 70.23 | - | model | log |
| DeepLabV3 | M-V2-D8 | 512x1024 | 80000 | 3.9 | 8.4 | 73.84 | - | model | log |
| DeepLabV3+ | M-V2-D8 | 512x1024 | 80000 | 5.1 | 8.4 | 75.20 | - | model | log |
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | download |
|---|---|---|---|---|---|---|---|---|
| FCN | M-V2-D8 | 512x512 | 160000 | 6.5 | 64.4 | 19.71 | - | model | log |
| PSPNet | M-V2-D8 | 512x512 | 160000 | 6.5 | 57.7 | 29.68 | - | model | log |
| DeepLabV3 | M-V2-D8 | 512x512 | 160000 | 6.8 | 39.9 | 34.08 | - | model | log |
| DeepLabV3+ | M-V2-D8 | 512x512 | 160000 | 8.2 | 43.1 | 34.02 | - | model | log |