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| Models: | |
| - Name: resnest_s101-d8_fcn_4xb2-80k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.56 | |
| mIoU(ms+flip): 78.98 | |
| Config: configs/resnest/resnest_s101-d8_fcn_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - S-101-D8 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 11.4 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/fcn_s101-d8_512x1024_80k_cityscapes/fcn_s101-d8_512x1024_80k_cityscapes_20200807_140631-f8d155b3.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/fcn_s101-d8_512x1024_80k_cityscapes/fcn_s101-d8_512x1024_80k_cityscapes-20200807_140631.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_pspnet_4xb2-80k_cityscapes512x1024 | |
| In Collection: PSPNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.57 | |
| mIoU(ms+flip): 79.19 | |
| Config: configs/resnest/resnest_s101-d8_pspnet_4xb2-80k_cityscapes512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - S-101-D8 | |
| - PSPNet | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 11.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/pspnet_s101-d8_512x1024_80k_cityscapes/pspnet_s101-d8_512x1024_80k_cityscapes_20200807_140631-c75f3b99.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/pspnet_s101-d8_512x1024_80k_cityscapes/pspnet_s101-d8_512x1024_80k_cityscapes-20200807_140631.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_deeplabv3_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.67 | |
| mIoU(ms+flip): 80.51 | |
| Config: configs/resnest/resnest_s101-d8_deeplabv3_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - S-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 11.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes/deeplabv3_s101-d8_512x1024_80k_cityscapes_20200807_144429-b73c4270.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes/deeplabv3_s101-d8_512x1024_80k_cityscapes-20200807_144429.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3+ | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.62 | |
| mIoU(ms+flip): 80.27 | |
| Config: configs/resnest/resnest_s101-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - S-101-D8 | |
| - DeepLabV3+ | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 13.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes/deeplabv3plus_s101-d8_512x1024_80k_cityscapes_20200807_144429-1239eb43.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes/deeplabv3plus_s101-d8_512x1024_80k_cityscapes-20200807_144429.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_fcn_4xb4-160k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.62 | |
| mIoU(ms+flip): 46.16 | |
| Config: configs/resnest/resnest_s101-d8_fcn_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - S-101-D8 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 14.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/fcn_s101-d8_512x512_160k_ade20k/fcn_s101-d8_512x512_160k_ade20k_20200807_145416-d3160329.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/fcn_s101-d8_512x512_160k_ade20k/fcn_s101-d8_512x512_160k_ade20k-20200807_145416.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_pspnet_4xb4-160k_ade20k-512x512 | |
| In Collection: PSPNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.44 | |
| mIoU(ms+flip): 46.28 | |
| Config: configs/resnest/resnest_s101-d8_pspnet_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - S-101-D8 | |
| - PSPNet | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 14.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/pspnet_s101-d8_512x512_160k_ade20k/pspnet_s101-d8_512x512_160k_ade20k_20200807_145416-a6daa92a.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/pspnet_s101-d8_512x512_160k_ade20k/pspnet_s101-d8_512x512_160k_ade20k-20200807_145416.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_deeplabv3_4xb4-160k_ade20k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.71 | |
| mIoU(ms+flip): 46.59 | |
| Config: configs/resnest/resnest_s101-d8_deeplabv3_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - S-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 14.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x512_160k_ade20k/deeplabv3_s101-d8_512x512_160k_ade20k_20200807_144503-17ecabe5.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x512_160k_ade20k/deeplabv3_s101-d8_512x512_160k_ade20k-20200807_144503.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |
| - Name: resnest_s101-d8_deeplabv3plus_4xb4-160k_ade20k-512x512 | |
| In Collection: DeepLabV3+ | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 46.47 | |
| mIoU(ms+flip): 47.27 | |
| Config: configs/resnest/resnest_s101-d8_deeplabv3plus_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - S-101-D8 | |
| - DeepLabV3+ | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 16.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x512_160k_ade20k/deeplabv3plus_s101-d8_512x512_160k_ade20k_20200807_144503-27b26226.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x512_160k_ade20k/deeplabv3plus_s101-d8_512x512_160k_ade20k-20200807_144503.log.json | |
| Paper: | |
| Title: 'ResNeSt: Split-Attention Networks' | |
| URL: https://arxiv.org/abs/2004.08955 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/resnest.py#L271 | |
| Framework: PyTorch | |