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Collections: | |
- Name: GCNet | |
License: Apache License 2.0 | |
Metadata: | |
Training Data: | |
- Cityscapes | |
- ADE20K | |
- Pascal VOC 2012 + Aug | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
README: configs/gcnet/README.md | |
Frameworks: | |
- PyTorch | |
Models: | |
- Name: gcnet_r50-d8_4xb2-40k_cityscapes-512x1024 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 77.69 | |
mIoU(ms+flip): 78.56 | |
Config: configs/gcnet/gcnet_r50-d8_4xb2-40k_cityscapes-512x1024.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 5.8 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x1024_40k_cityscapes/gcnet_r50-d8_512x1024_40k_cityscapes_20200618_074436-4b0fd17b.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x1024_40k_cityscapes/gcnet_r50-d8_512x1024_40k_cityscapes_20200618_074436.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb2-40k_cityscapes-512x1024 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 78.28 | |
mIoU(ms+flip): 79.34 | |
Config: configs/gcnet/gcnet_r101-d8_4xb2-40k_cityscapes-512x1024.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 9.2 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x1024_40k_cityscapes/gcnet_r101-d8_512x1024_40k_cityscapes_20200618_074436-5e62567f.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x1024_40k_cityscapes/gcnet_r101-d8_512x1024_40k_cityscapes_20200618_074436.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb2-40k_cityscapes-769x769 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 78.12 | |
mIoU(ms+flip): 80.09 | |
Config: configs/gcnet/gcnet_r50-d8_4xb2-40k_cityscapes-769x769.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 6.5 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_769x769_40k_cityscapes/gcnet_r50-d8_769x769_40k_cityscapes_20200618_182814-a26f4471.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_769x769_40k_cityscapes/gcnet_r50-d8_769x769_40k_cityscapes_20200618_182814.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb2-40k_cityscapes-769x769 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 78.95 | |
mIoU(ms+flip): 80.71 | |
Config: configs/gcnet/gcnet_r101-d8_4xb2-40k_cityscapes-769x769.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 10.5 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_769x769_40k_cityscapes/gcnet_r101-d8_769x769_40k_cityscapes_20200619_092550-ca4f0a84.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_769x769_40k_cityscapes/gcnet_r101-d8_769x769_40k_cityscapes_20200619_092550.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb2-80k_cityscapes-512x1024 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 78.48 | |
mIoU(ms+flip): 80.01 | |
Config: configs/gcnet/gcnet_r50-d8_4xb2-80k_cityscapes-512x1024.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes/gcnet_r50-d8_512x1024_80k_cityscapes_20200618_074450-ef8f069b.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes/gcnet_r50-d8_512x1024_80k_cityscapes_20200618_074450.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb2-80k_cityscapes-512x1024 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 79.03 | |
mIoU(ms+flip): 79.84 | |
Config: configs/gcnet/gcnet_r101-d8_4xb2-80k_cityscapes-512x1024.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x1024_80k_cityscapes/gcnet_r101-d8_512x1024_80k_cityscapes_20200618_074450-778ebf69.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x1024_80k_cityscapes/gcnet_r101-d8_512x1024_80k_cityscapes_20200618_074450.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb2-80k_cityscapes-769x769 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 78.68 | |
mIoU(ms+flip): 80.66 | |
Config: configs/gcnet/gcnet_r50-d8_4xb2-80k_cityscapes-769x769.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_769x769_80k_cityscapes/gcnet_r50-d8_769x769_80k_cityscapes_20200619_092516-4839565b.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_769x769_80k_cityscapes/gcnet_r50-d8_769x769_80k_cityscapes_20200619_092516.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb2-80k_cityscapes-769x769 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Cityscapes | |
Metrics: | |
mIoU: 79.18 | |
mIoU(ms+flip): 80.71 | |
Config: configs/gcnet/gcnet_r101-d8_4xb2-80k_cityscapes-769x769.py | |
Metadata: | |
Training Data: Cityscapes | |
Batch Size: 8 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_769x769_80k_cityscapes/gcnet_r101-d8_769x769_80k_cityscapes_20200619_092628-8e043423.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_769x769_80k_cityscapes/gcnet_r101-d8_769x769_80k_cityscapes_20200619_092628.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb4-80k_ade20k-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: ADE20K | |
Metrics: | |
mIoU: 41.47 | |
mIoU(ms+flip): 42.85 | |
Config: configs/gcnet/gcnet_r50-d8_4xb4-80k_ade20k-512x512.py | |
Metadata: | |
Training Data: ADE20K | |
Batch Size: 16 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 8.5 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_80k_ade20k/gcnet_r50-d8_512x512_80k_ade20k_20200614_185146-91a6da41.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_80k_ade20k/gcnet_r50-d8_512x512_80k_ade20k_20200614_185146.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb4-80k_ade20k-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: ADE20K | |
Metrics: | |
mIoU: 42.82 | |
mIoU(ms+flip): 44.54 | |
Config: configs/gcnet/gcnet_r101-d8_4xb4-80k_ade20k-512x512.py | |
Metadata: | |
Training Data: ADE20K | |
Batch Size: 16 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 12.0 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_80k_ade20k/gcnet_r101-d8_512x512_80k_ade20k_20200615_020811-c3fcb6dd.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_80k_ade20k/gcnet_r101-d8_512x512_80k_ade20k_20200615_020811.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb4-160k_ade20k-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: ADE20K | |
Metrics: | |
mIoU: 42.37 | |
mIoU(ms+flip): 43.52 | |
Config: configs/gcnet/gcnet_r50-d8_4xb4-160k_ade20k-512x512.py | |
Metadata: | |
Training Data: ADE20K | |
Batch Size: 16 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_160k_ade20k/gcnet_r50-d8_512x512_160k_ade20k_20200615_224122-d95f3e1f.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_160k_ade20k/gcnet_r50-d8_512x512_160k_ade20k_20200615_224122.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb4-160k_ade20k-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: ADE20K | |
Metrics: | |
mIoU: 43.69 | |
mIoU(ms+flip): 45.21 | |
Config: configs/gcnet/gcnet_r101-d8_4xb4-160k_ade20k-512x512.py | |
Metadata: | |
Training Data: ADE20K | |
Batch Size: 16 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_160k_ade20k/gcnet_r101-d8_512x512_160k_ade20k_20200615_225406-615528d7.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_160k_ade20k/gcnet_r101-d8_512x512_160k_ade20k_20200615_225406.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb4-20k_voc12aug-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Pascal VOC 2012 + Aug | |
Metrics: | |
mIoU: 76.42 | |
mIoU(ms+flip): 77.51 | |
Config: configs/gcnet/gcnet_r50-d8_4xb4-20k_voc12aug-512x512.py | |
Metadata: | |
Training Data: Pascal VOC 2012 + Aug | |
Batch Size: 16 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 5.8 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_20k_voc12aug/gcnet_r50-d8_512x512_20k_voc12aug_20200617_165701-3cbfdab1.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_20k_voc12aug/gcnet_r50-d8_512x512_20k_voc12aug_20200617_165701.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb4-20k_voc12aug-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Pascal VOC 2012 + Aug | |
Metrics: | |
mIoU: 77.41 | |
mIoU(ms+flip): 78.56 | |
Config: configs/gcnet/gcnet_r101-d8_4xb4-20k_voc12aug-512x512.py | |
Metadata: | |
Training Data: Pascal VOC 2012 + Aug | |
Batch Size: 16 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Memory (GB): 9.2 | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_20k_voc12aug/gcnet_r101-d8_512x512_20k_voc12aug_20200617_165713-6c720aa9.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_20k_voc12aug/gcnet_r101-d8_512x512_20k_voc12aug_20200617_165713.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r50-d8_4xb4-40k_voc12aug-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Pascal VOC 2012 + Aug | |
Metrics: | |
mIoU: 76.24 | |
mIoU(ms+flip): 77.63 | |
Config: configs/gcnet/gcnet_r50-d8_4xb4-40k_voc12aug-512x512.py | |
Metadata: | |
Training Data: Pascal VOC 2012 + Aug | |
Batch Size: 16 | |
Architecture: | |
- R-50-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_40k_voc12aug/gcnet_r50-d8_512x512_40k_voc12aug_20200613_195105-9797336d.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r50-d8_512x512_40k_voc12aug/gcnet_r50-d8_512x512_40k_voc12aug_20200613_195105.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |
- Name: gcnet_r101-d8_4xb4-40k_voc12aug-512x512 | |
In Collection: GCNet | |
Results: | |
Task: Semantic Segmentation | |
Dataset: Pascal VOC 2012 + Aug | |
Metrics: | |
mIoU: 77.84 | |
mIoU(ms+flip): 78.59 | |
Config: configs/gcnet/gcnet_r101-d8_4xb4-40k_voc12aug-512x512.py | |
Metadata: | |
Training Data: Pascal VOC 2012 + Aug | |
Batch Size: 16 | |
Architecture: | |
- R-101-D8 | |
- GCNet | |
Training Resources: 4x V100 GPUS | |
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_40k_voc12aug/gcnet_r101-d8_512x512_40k_voc12aug_20200613_185806-1e38208d.pth | |
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/gcnet/gcnet_r101-d8_512x512_40k_voc12aug/gcnet_r101-d8_512x512_40k_voc12aug_20200613_185806.log.json | |
Paper: | |
Title: 'GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond' | |
URL: https://arxiv.org/abs/1904.11492 | |
Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/gc_head.py#L10 | |
Framework: PyTorch | |