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| Collections: | |
| - Name: ANN | |
| License: Apache License 2.0 | |
| Metadata: | |
| Training Data: | |
| - Cityscapes | |
| - ADE20K | |
| - Pascal VOC 2012 + Aug | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| README: configs/ann/README.md | |
| Frameworks: | |
| - PyTorch | |
| Models: | |
| - Name: ann_r50-d8_4xb2-40k_cityscapes-512x1024 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.4 | |
| mIoU(ms+flip): 78.57 | |
| Config: configs/ann/ann_r50-d8_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.0 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x1024_40k_cityscapes/ann_r50-d8_512x1024_40k_cityscapes_20200605_095211-049fc292.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x1024_40k_cityscapes/ann_r50-d8_512x1024_40k_cityscapes_20200605_095211.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb2-40k_cityscapes-512x1024 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.55 | |
| mIoU(ms+flip): 78.85 | |
| Config: configs/ann/ann_r101-d8_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x1024_40k_cityscapes/ann_r101-d8_512x1024_40k_cityscapes_20200605_095243-adf6eece.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x1024_40k_cityscapes/ann_r101-d8_512x1024_40k_cityscapes_20200605_095243.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb2-40k_cityscapes-769x769 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.89 | |
| mIoU(ms+flip): 80.46 | |
| Config: configs/ann/ann_r50-d8_4xb2-40k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_769x769_40k_cityscapes/ann_r50-d8_769x769_40k_cityscapes_20200530_025712-2b46b04d.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_769x769_40k_cityscapes/ann_r50-d8_769x769_40k_cityscapes_20200530_025712.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb2-40k_cityscapes-769x769 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.32 | |
| mIoU(ms+flip): 80.94 | |
| Config: configs/ann/ann_r101-d8_4xb2-40k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 10.7 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_769x769_40k_cityscapes/ann_r101-d8_769x769_40k_cityscapes_20200530_025720-059bff28.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_769x769_40k_cityscapes/ann_r101-d8_769x769_40k_cityscapes_20200530_025720.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.34 | |
| mIoU(ms+flip): 78.65 | |
| Config: configs/ann/ann_r50-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x1024_80k_cityscapes/ann_r50-d8_512x1024_80k_cityscapes_20200607_101911-5a9ad545.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x1024_80k_cityscapes/ann_r50-d8_512x1024_80k_cityscapes_20200607_101911.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.14 | |
| mIoU(ms+flip): 78.81 | |
| Config: configs/ann/ann_r101-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x1024_80k_cityscapes/ann_r101-d8_512x1024_80k_cityscapes_20200607_013728-aceccc6e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x1024_80k_cityscapes/ann_r101-d8_512x1024_80k_cityscapes_20200607_013728.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.88 | |
| mIoU(ms+flip): 80.57 | |
| Config: configs/ann/ann_r50-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_769x769_80k_cityscapes/ann_r50-d8_769x769_80k_cityscapes_20200607_044426-cc7ff323.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_769x769_80k_cityscapes/ann_r50-d8_769x769_80k_cityscapes_20200607_044426.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.8 | |
| mIoU(ms+flip): 80.34 | |
| Config: configs/ann/ann_r101-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_769x769_80k_cityscapes/ann_r101-d8_769x769_80k_cityscapes_20200607_013713-a9d4be8d.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_769x769_80k_cityscapes/ann_r101-d8_769x769_80k_cityscapes_20200607_013713.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb4-80k_ade20k-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 41.01 | |
| mIoU(ms+flip): 42.3 | |
| Config: configs/ann/ann_r50-d8_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.1 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_80k_ade20k/ann_r50-d8_512x512_80k_ade20k_20200615_014818-26f75e11.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_80k_ade20k/ann_r50-d8_512x512_80k_ade20k_20200615_014818.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb4-80k_ade20k-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 42.94 | |
| mIoU(ms+flip): 44.18 | |
| Config: configs/ann/ann_r101-d8_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 12.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_80k_ade20k/ann_r101-d8_512x512_80k_ade20k_20200615_014818-c0153543.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_80k_ade20k/ann_r101-d8_512x512_80k_ade20k_20200615_014818.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb4-160k_ade20k-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 41.74 | |
| mIoU(ms+flip): 42.62 | |
| Config: configs/ann/ann_r50-d8_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_160k_ade20k/ann_r50-d8_512x512_160k_ade20k_20200615_231733-892247bc.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_160k_ade20k/ann_r50-d8_512x512_160k_ade20k_20200615_231733.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb4-160k_ade20k-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 42.94 | |
| mIoU(ms+flip): 44.06 | |
| Config: configs/ann/ann_r101-d8_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_160k_ade20k/ann_r101-d8_512x512_160k_ade20k_20200615_231733-955eb1ec.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_160k_ade20k/ann_r101-d8_512x512_160k_ade20k_20200615_231733.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb4-20k_voc12aug-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 74.86 | |
| mIoU(ms+flip): 76.13 | |
| Config: configs/ann/ann_r50-d8_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.0 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_20k_voc12aug/ann_r50-d8_512x512_20k_voc12aug_20200617_222246-dfcb1c62.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_20k_voc12aug/ann_r50-d8_512x512_20k_voc12aug_20200617_222246.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb4-20k_voc12aug-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 77.47 | |
| mIoU(ms+flip): 78.7 | |
| Config: configs/ann/ann_r101-d8_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_20k_voc12aug/ann_r101-d8_512x512_20k_voc12aug_20200617_222246-2fad0042.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_20k_voc12aug/ann_r101-d8_512x512_20k_voc12aug_20200617_222246.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r50-d8_4xb4-40k_voc12aug-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 76.56 | |
| mIoU(ms+flip): 77.51 | |
| Config: configs/ann/ann_r50-d8_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_40k_voc12aug/ann_r50-d8_512x512_40k_voc12aug_20200613_231314-b5dac322.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_40k_voc12aug/ann_r50-d8_512x512_40k_voc12aug_20200613_231314.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |
| - Name: ann_r101-d8_4xb4-40k_voc12aug-512x512 | |
| In Collection: ANN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 76.7 | |
| mIoU(ms+flip): 78.06 | |
| Config: configs/ann/ann_r101-d8_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - ANN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_40k_voc12aug/ann_r101-d8_512x512_40k_voc12aug_20200613_231314-bd205bbe.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_40k_voc12aug/ann_r101-d8_512x512_40k_voc12aug_20200613_231314.log.json | |
| Paper: | |
| Title: Asymmetric Non-local Neural Networks for Semantic Segmentation | |
| URL: https://arxiv.org/abs/1908.07678 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/ann_head.py#L185 | |
| Framework: PyTorch | |