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Collections: |
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- Name: BiSeNetV2 |
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License: Apache License 2.0 |
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Metadata: |
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Training Data: |
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- Cityscapes |
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Paper: |
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Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic |
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Segmentation' |
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URL: https://arxiv.org/abs/2004.02147 |
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README: configs/bisenetv2/README.md |
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Frameworks: |
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- PyTorch |
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Models: |
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- Name: bisenetv2_fcn_4xb4-160k_cityscapes-1024x1024 |
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In Collection: BiSeNetV2 |
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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: 73.21 |
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mIoU(ms+flip): 75.74 |
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Config: configs/bisenetv2/bisenetv2_fcn_4xb4-160k_cityscapes-1024x1024.py |
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Metadata: |
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Training Data: Cityscapes |
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Batch Size: 16 |
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Architecture: |
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- BiSeNetV2 |
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- BiSeNetV2 |
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Training Resources: 4x V100 GPUS |
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Memory (GB): 7.64 |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes_20210902_015551-bcf10f09.pth |
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Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes_20210902_015551.log.json |
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Paper: |
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Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic |
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Segmentation' |
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URL: https://arxiv.org/abs/2004.02147 |
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Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545 |
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Framework: PyTorch |
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- Name: bisenetv2_fcn_4xb4-ohem-160k_cityscapes-1024x1024 |
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In Collection: BiSeNetV2 |
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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: 73.57 |
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mIoU(ms+flip): 75.8 |
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Config: configs/bisenetv2/bisenetv2_fcn_4xb4-ohem-160k_cityscapes-1024x1024.py |
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Metadata: |
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Training Data: Cityscapes |
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Batch Size: 16 |
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Architecture: |
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- BiSeNetV2 |
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- BiSeNetV2 |
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Training Resources: 4x V100 GPUS |
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Memory (GB): 7.64 |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes_20210902_112947-5f8103b4.pth |
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Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes_20210902_112947.log.json |
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Paper: |
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Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic |
|
Segmentation' |
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URL: https://arxiv.org/abs/2004.02147 |
|
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545 |
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Framework: PyTorch |
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- Name: bisenetv2_fcn_4xb8-160k_cityscapes-1024x1024 |
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In Collection: BiSeNetV2 |
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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: 75.76 |
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mIoU(ms+flip): 77.79 |
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Config: configs/bisenetv2/bisenetv2_fcn_4xb8-160k_cityscapes-1024x1024.py |
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Metadata: |
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Training Data: Cityscapes |
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Batch Size: 32 |
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Architecture: |
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- BiSeNetV2 |
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- BiSeNetV2 |
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Training Resources: 4x V100 GPUS |
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Memory (GB): 15.05 |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes_20210903_000032-e1a2eed6.pth |
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Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes_20210903_000032.log.json |
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Paper: |
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Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic |
|
Segmentation' |
|
URL: https://arxiv.org/abs/2004.02147 |
|
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545 |
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Framework: PyTorch |
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- Name: bisenetv2_fcn_4xb4-amp-160k_cityscapes-1024x1024 |
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In Collection: BiSeNetV2 |
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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: 73.07 |
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mIoU(ms+flip): 75.13 |
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Config: configs/bisenetv2/bisenetv2_fcn_4xb4-amp-160k_cityscapes-1024x1024.py |
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Metadata: |
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Training Data: Cityscapes |
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Batch Size: 16 |
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Architecture: |
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- BiSeNetV2 |
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- BiSeNetV2 |
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Training Resources: 4x V100 GPUS |
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Memory (GB): 5.77 |
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes_20210902_045942-b979777b.pth |
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Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes_20210902_045942.log.json |
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Paper: |
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Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic |
|
Segmentation' |
|
URL: https://arxiv.org/abs/2004.02147 |
|
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545 |
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Framework: PyTorch |
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