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Collections: |
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- Name: dmnet |
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Metadata: |
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Training Data: |
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- Cityscapes |
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- ADE20K |
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Paper: |
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URL: https://openaccess.thecvf.com/content_ICCV_2019/papers/He_Dynamic_Multi-Scale_Filters_for_Semantic_Segmentation_ICCV_2019_paper.pdf |
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Title: Dynamic Multi-scale Filters for Semantic Segmentation |
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README: configs/dmnet/README.md |
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Code: |
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URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/dm_head.py#L93 |
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Version: v0.17.0 |
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Converted From: |
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Code: https://github.com/Junjun2016/DMNet |
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Models: |
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- Name: dmnet_r50-d8_512x1024_40k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-50-D8 |
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crop size: (512,1024) |
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lr schd: 40000 |
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inference time (ms/im): |
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- value: 273.22 |
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hardware: V100 |
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backend: PyTorch |
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batch size: 1 |
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mode: FP32 |
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resolution: (512,1024) |
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Training Memory (GB): 7.0 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 77.78 |
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mIoU(ms+flip): 79.14 |
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Config: configs/dmnet/dmnet_r50-d8_512x1024_40k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r50-d8_512x1024_40k_cityscapes/dmnet_r50-d8_512x1024_40k_cityscapes_20201215_042326-615373cf.pth |
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- Name: dmnet_r101-d8_512x1024_40k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-101-D8 |
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crop size: (512,1024) |
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lr schd: 40000 |
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inference time (ms/im): |
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- value: 393.7 |
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hardware: V100 |
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backend: PyTorch |
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batch size: 1 |
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mode: FP32 |
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resolution: (512,1024) |
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Training Memory (GB): 10.6 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 78.37 |
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mIoU(ms+flip): 79.72 |
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Config: configs/dmnet/dmnet_r101-d8_512x1024_40k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r101-d8_512x1024_40k_cityscapes/dmnet_r101-d8_512x1024_40k_cityscapes_20201215_043100-8291e976.pth |
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- Name: dmnet_r50-d8_769x769_40k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-50-D8 |
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crop size: (769,769) |
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lr schd: 40000 |
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inference time (ms/im): |
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- value: 636.94 |
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hardware: V100 |
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backend: PyTorch |
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batch size: 1 |
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mode: FP32 |
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resolution: (769,769) |
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Training Memory (GB): 7.9 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 78.49 |
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mIoU(ms+flip): 80.27 |
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Config: configs/dmnet/dmnet_r50-d8_769x769_40k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r50-d8_769x769_40k_cityscapes/dmnet_r50-d8_769x769_40k_cityscapes_20201215_093706-e7f0e23e.pth |
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- Name: dmnet_r101-d8_769x769_40k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-101-D8 |
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crop size: (769,769) |
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lr schd: 40000 |
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inference time (ms/im): |
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- value: 990.1 |
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hardware: V100 |
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backend: PyTorch |
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batch size: 1 |
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mode: FP32 |
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resolution: (769,769) |
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Training Memory (GB): 12.0 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 77.62 |
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mIoU(ms+flip): 78.94 |
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Config: configs/dmnet/dmnet_r101-d8_769x769_40k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r101-d8_769x769_40k_cityscapes/dmnet_r101-d8_769x769_40k_cityscapes_20201215_081348-a74261f6.pth |
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- Name: dmnet_r50-d8_512x1024_80k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-50-D8 |
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crop size: (512,1024) |
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lr schd: 80000 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 79.07 |
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mIoU(ms+flip): 80.22 |
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Config: configs/dmnet/dmnet_r50-d8_512x1024_80k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r50-d8_512x1024_80k_cityscapes/dmnet_r50-d8_512x1024_80k_cityscapes_20201215_053728-3c8893b9.pth |
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- Name: dmnet_r101-d8_512x1024_80k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-101-D8 |
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crop size: (512,1024) |
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lr schd: 80000 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 79.64 |
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mIoU(ms+flip): 80.67 |
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Config: configs/dmnet/dmnet_r101-d8_512x1024_80k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r101-d8_512x1024_80k_cityscapes/dmnet_r101-d8_512x1024_80k_cityscapes_20201215_031718-fa081cb8.pth |
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- Name: dmnet_r50-d8_769x769_80k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-50-D8 |
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crop size: (769,769) |
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lr schd: 80000 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 79.22 |
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mIoU(ms+flip): 80.55 |
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Config: configs/dmnet/dmnet_r50-d8_769x769_80k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r50-d8_769x769_80k_cityscapes/dmnet_r50-d8_769x769_80k_cityscapes_20201215_034006-6060840e.pth |
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- Name: dmnet_r101-d8_769x769_80k_cityscapes |
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In Collection: dmnet |
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Metadata: |
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backbone: R-101-D8 |
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crop size: (769,769) |
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lr schd: 80000 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: Cityscapes |
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Metrics: |
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mIoU: 79.19 |
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mIoU(ms+flip): 80.65 |
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Config: configs/dmnet/dmnet_r101-d8_769x769_80k_cityscapes.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r101-d8_769x769_80k_cityscapes/dmnet_r101-d8_769x769_80k_cityscapes_20201215_082810-7f0de59a.pth |
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- Name: dmnet_r50-d8_512x512_80k_ade20k |
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In Collection: dmnet |
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Metadata: |
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backbone: R-50-D8 |
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crop size: (512,512) |
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lr schd: 80000 |
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inference time (ms/im): |
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- value: 47.73 |
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hardware: V100 |
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backend: PyTorch |
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batch size: 1 |
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mode: FP32 |
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resolution: (512,512) |
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Training Memory (GB): 9.4 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: ADE20K |
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Metrics: |
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mIoU: 42.37 |
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mIoU(ms+flip): 43.62 |
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Config: configs/dmnet/dmnet_r50-d8_512x512_80k_ade20k.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r50-d8_512x512_80k_ade20k/dmnet_r50-d8_512x512_80k_ade20k_20201215_144744-f89092a6.pth |
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- Name: dmnet_r101-d8_512x512_80k_ade20k |
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In Collection: dmnet |
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Metadata: |
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backbone: R-101-D8 |
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crop size: (512,512) |
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lr schd: 80000 |
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inference time (ms/im): |
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- value: 72.05 |
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hardware: V100 |
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backend: PyTorch |
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batch size: 1 |
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mode: FP32 |
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resolution: (512,512) |
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Training Memory (GB): 13.0 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: ADE20K |
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Metrics: |
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mIoU: 45.34 |
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mIoU(ms+flip): 46.13 |
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Config: configs/dmnet/dmnet_r101-d8_512x512_80k_ade20k.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r101-d8_512x512_80k_ade20k/dmnet_r101-d8_512x512_80k_ade20k_20201215_104812-bfa45311.pth |
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- Name: dmnet_r50-d8_512x512_160k_ade20k |
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In Collection: dmnet |
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Metadata: |
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backbone: R-50-D8 |
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crop size: (512,512) |
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lr schd: 160000 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: ADE20K |
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Metrics: |
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mIoU: 43.15 |
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mIoU(ms+flip): 44.17 |
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Config: configs/dmnet/dmnet_r50-d8_512x512_160k_ade20k.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r50-d8_512x512_160k_ade20k/dmnet_r50-d8_512x512_160k_ade20k_20201215_115313-025ab3f9.pth |
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- Name: dmnet_r101-d8_512x512_160k_ade20k |
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In Collection: dmnet |
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Metadata: |
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backbone: R-101-D8 |
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crop size: (512,512) |
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lr schd: 160000 |
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Results: |
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- Task: Semantic Segmentation |
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Dataset: ADE20K |
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Metrics: |
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mIoU: 45.42 |
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mIoU(ms+flip): 46.76 |
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Config: configs/dmnet/dmnet_r101-d8_512x512_160k_ade20k.py |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/dmnet/dmnet_r101-d8_512x512_160k_ade20k/dmnet_r101-d8_512x512_160k_ade20k_20201215_111145-a0bc02ef.pth |