| Models: | |
| - Name: fcn_hr18s_4xb2-40k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 73.86 | |
| mIoU(ms+flip): 75.91 | |
| Config: configs/hrnet/fcn_hr18s_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.7 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_40k_cityscapes/fcn_hr18s_512x1024_40k_cityscapes_20200601_014216-93db27d0.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_40k_cityscapes/fcn_hr18s_512x1024_40k_cityscapes_20200601_014216.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb2-40k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.19 | |
| mIoU(ms+flip): 78.92 | |
| Config: configs/hrnet/fcn_hr18_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 2.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_40k_cityscapes/fcn_hr18_512x1024_40k_cityscapes_20200601_014216-f196fb4e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_40k_cityscapes/fcn_hr18_512x1024_40k_cityscapes_20200601_014216.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb2-40k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.48 | |
| mIoU(ms+flip): 79.69 | |
| Config: configs/hrnet/fcn_hr48_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_40k_cityscapes/fcn_hr48_512x1024_40k_cityscapes_20200601_014240-a989b146.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_40k_cityscapes/fcn_hr48_512x1024_40k_cityscapes_20200601_014240.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb2-80k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 75.31 | |
| mIoU(ms+flip): 77.48 | |
| Config: configs/hrnet/fcn_hr18s_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_80k_cityscapes/fcn_hr18s_512x1024_80k_cityscapes_20200601_202700-1462b75d.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_80k_cityscapes/fcn_hr18s_512x1024_80k_cityscapes_20200601_202700.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb2-80k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.65 | |
| mIoU(ms+flip): 80.35 | |
| Config: configs/hrnet/fcn_hr18_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_80k_cityscapes/fcn_hr18_512x1024_80k_cityscapes_20200601_223255-4e7b345e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_80k_cityscapes/fcn_hr18_512x1024_80k_cityscapes_20200601_223255.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb2-80k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.93 | |
| mIoU(ms+flip): 80.72 | |
| Config: configs/hrnet/fcn_hr48_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_80k_cityscapes/fcn_hr48_512x1024_80k_cityscapes_20200601_202606-58ea95d6.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_80k_cityscapes/fcn_hr48_512x1024_80k_cityscapes_20200601_202606.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb2-160k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.31 | |
| mIoU(ms+flip): 78.31 | |
| Config: configs/hrnet/fcn_hr18s_4xb2-160k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_160k_cityscapes/fcn_hr18s_512x1024_160k_cityscapes_20200602_190901-4a0797ea.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_160k_cityscapes/fcn_hr18s_512x1024_160k_cityscapes_20200602_190901.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb2-160k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.8 | |
| mIoU(ms+flip): 80.74 | |
| Config: configs/hrnet/fcn_hr18_4xb2-160k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_160k_cityscapes/fcn_hr18_512x1024_160k_cityscapes_20200602_190822-221e4a4f.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_160k_cityscapes/fcn_hr18_512x1024_160k_cityscapes_20200602_190822.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb2-160k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 80.65 | |
| mIoU(ms+flip): 81.92 | |
| Config: configs/hrnet/fcn_hr48_4xb2-160k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_160k_cityscapes/fcn_hr48_512x1024_160k_cityscapes_20200602_190946-59b7973e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_160k_cityscapes/fcn_hr48_512x1024_160k_cityscapes_20200602_190946.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-80k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 31.38 | |
| mIoU(ms+flip): 32.45 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 3.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_ade20k/fcn_hr18s_512x512_80k_ade20k_20200614_144345-77fc814a.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_ade20k/fcn_hr18s_512x512_80k_ade20k_20200614_144345.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-80k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 36.27 | |
| mIoU(ms+flip): 37.28 | |
| Config: configs/hrnet/fcn_hr18_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 4.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_ade20k/fcn_hr18_512x512_80k_ade20k_20210827_114910-6c9382c0.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_ade20k/fcn_hr18_512x512_80k_ade20k_20210827_114910.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 41.9 | |
| mIoU(ms+flip): 43.27 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 8.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_ade20k/fcn_hr48_512x512_80k_ade20k_20200614_193946-7ba5258d.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_ade20k/fcn_hr48_512x512_80k_ade20k_20200614_193946.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-160k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 33.07 | |
| mIoU(ms+flip): 34.56 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_160k_ade20k/fcn_hr18s_512x512_160k_ade20k_20210829_174739-f1e7c2e7.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_160k_ade20k/fcn_hr18s_512x512_160k_ade20k_20210829_174739.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-160k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 36.79 | |
| mIoU(ms+flip): 38.58 | |
| Config: configs/hrnet/fcn_hr18_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_160k_ade20k/fcn_hr18_512x512_160k_ade20k_20200614_214426-ca961836.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_160k_ade20k/fcn_hr18_512x512_160k_ade20k_20200614_214426.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-160k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 42.02 | |
| mIoU(ms+flip): 43.86 | |
| Config: configs/hrnet/fcn_hr48_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_160k_ade20k/fcn_hr48_512x512_160k_ade20k_20200614_214407-a52fc02c.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_160k_ade20k/fcn_hr48_512x512_160k_ade20k_20200614_214407.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-20k_voc12aug-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 65.5 | |
| mIoU(ms+flip): 68.89 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_20k_voc12aug/fcn_hr18s_512x512_20k_voc12aug_20210829_174910-0aceadb4.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_20k_voc12aug/fcn_hr18s_512x512_20k_voc12aug_20210829_174910.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-20k_voc12aug-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 72.3 | |
| mIoU(ms+flip): 74.71 | |
| Config: configs/hrnet/fcn_hr18_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 2.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_20k_voc12aug/fcn_hr18_512x512_20k_voc12aug_20200617_224503-488d45f7.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_20k_voc12aug/fcn_hr18_512x512_20k_voc12aug_20200617_224503.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-20k_voc12aug-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 75.87 | |
| mIoU(ms+flip): 78.58 | |
| Config: configs/hrnet/fcn_hr48_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_20k_voc12aug/fcn_hr48_512x512_20k_voc12aug_20200617_224419-89de05cd.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_20k_voc12aug/fcn_hr48_512x512_20k_voc12aug_20200617_224419.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-40k_voc12aug-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 66.61 | |
| mIoU(ms+flip): 70.0 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_40k_voc12aug/fcn_hr18s_512x512_40k_voc12aug_20200614_000648-4f8d6e7f.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_40k_voc12aug/fcn_hr18s_512x512_40k_voc12aug_20200614_000648.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-40k_voc12aug-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 72.9 | |
| mIoU(ms+flip): 75.59 | |
| Config: configs/hrnet/fcn_hr18_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_40k_voc12aug/fcn_hr18_512x512_40k_voc12aug_20200613_224401-1b4b76cd.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_40k_voc12aug/fcn_hr18_512x512_40k_voc12aug_20200613_224401.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-40k_voc12aug-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 76.24 | |
| mIoU(ms+flip): 78.49 | |
| Config: configs/hrnet/fcn_hr48_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_40k_voc12aug/fcn_hr48_512x512_40k_voc12aug_20200613_222111-1b0f18bc.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_40k_voc12aug/fcn_hr48_512x512_40k_voc12aug_20200613_222111.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-40k_pascal-context-480x480 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context | |
| Metrics: | |
| mIoU: 45.14 | |
| mIoU(ms+flip): 47.42 | |
| Config: configs/hrnet/fcn_hr48_4xb4-40k_pascal-context-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.1 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_40k_pascal_context/fcn_hr48_480x480_40k_pascal_context_20200911_164852-667d00b0.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_40k_pascal_context/fcn_hr48_480x480_40k_pascal_context-20200911_164852.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_pascal-context-480x480 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context | |
| Metrics: | |
| mIoU: 45.84 | |
| mIoU(ms+flip): 47.84 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_pascal-context-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_80k_pascal_context/fcn_hr48_480x480_80k_pascal_context_20200911_155322-847a6711.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_80k_pascal_context/fcn_hr48_480x480_80k_pascal_context-20200911_155322.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-40k_pascal-context-59-480x480 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context 59 | |
| Metrics: | |
| mIoU: 50.33 | |
| mIoU(ms+flip): 52.83 | |
| Config: configs/hrnet/fcn_hr48_4xb4-40k_pascal-context-59-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context 59 | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_40k_pascal_context_59/fcn_hr48_480x480_40k_pascal_context_59_20210410_122738-b808b8b2.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_40k_pascal_context_59/fcn_hr48_480x480_40k_pascal_context_59-20210410_122738.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_pascal-context-59-480x480 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context 59 | |
| Metrics: | |
| mIoU: 51.12 | |
| mIoU(ms+flip): 53.56 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_pascal-context-59-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context 59 | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_80k_pascal_context_59/fcn_hr48_480x480_80k_pascal_context_59_20210411_003240-3ae7081e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_80k_pascal_context_59/fcn_hr48_480x480_80k_pascal_context_59-20210411_003240.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-80k_loveda-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: LoveDA | |
| Metrics: | |
| mIoU: 49.28 | |
| mIoU(ms+flip): 49.42 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-80k_loveda-512x512.py | |
| Metadata: | |
| Training Data: LoveDA | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.59 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228-60a86a7a.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-80k_loveda-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: LoveDA | |
| Metrics: | |
| mIoU: 50.81 | |
| mIoU(ms+flip): 50.95 | |
| Config: configs/hrnet/fcn_hr18_4xb4-80k_loveda-512x512.py | |
| Metadata: | |
| Training Data: LoveDA | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 2.76 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952-93d9c3b3.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_loveda-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: LoveDA | |
| Metrics: | |
| mIoU: 51.42 | |
| mIoU(ms+flip): 51.64 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_loveda-512x512.py | |
| Metadata: | |
| Training Data: LoveDA | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756-67072f55.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-80k_potsdam-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Potsdam | |
| Metrics: | |
| mIoU: 77.64 | |
| mIoU(ms+flip): 78.8 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-80k_potsdam-512x512.py | |
| Metadata: | |
| Training Data: Potsdam | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.58 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_potsdam/fcn_hr18s_512x512_80k_potsdam_20211218_205517-ba32af63.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_potsdam/fcn_hr18s_512x512_80k_potsdam_20211218_205517.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-80k_potsdam-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Potsdam | |
| Metrics: | |
| mIoU: 78.26 | |
| mIoU(ms+flip): 79.24 | |
| Config: configs/hrnet/fcn_hr18_4xb4-80k_potsdam-512x512.py | |
| Metadata: | |
| Training Data: Potsdam | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 2.76 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_potsdam/fcn_hr18_512x512_80k_potsdam_20211218_205517-5d0387ad.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_potsdam/fcn_hr18_512x512_80k_potsdam_20211218_205517.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_potsdam-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Potsdam | |
| Metrics: | |
| mIoU: 78.39 | |
| mIoU(ms+flip): 79.34 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_potsdam-512x512.py | |
| Metadata: | |
| Training Data: Potsdam | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_potsdam/fcn_hr48_512x512_80k_potsdam_20211219_020601-97434c78.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_potsdam/fcn_hr48_512x512_80k_potsdam_20211219_020601.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-80k_vaihingen-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Vaihingen | |
| Metrics: | |
| mIoU: 71.81 | |
| mIoU(ms+flip): 73.1 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-80k_vaihingen-512x512.py | |
| Metadata: | |
| Training Data: Vaihingen | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.58 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_4x4_512x512_80k_vaihingen/fcn_hr18s_4x4_512x512_80k_vaihingen_20211231_230909-b23aae02.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_4x4_512x512_80k_vaihingen/fcn_hr18s_4x4_512x512_80k_vaihingen_20211231_230909.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-80k_vaihingen-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Vaihingen | |
| Metrics: | |
| mIoU: 72.57 | |
| mIoU(ms+flip): 74.09 | |
| Config: configs/hrnet/fcn_hr18_4xb4-80k_vaihingen-512x512.py | |
| Metadata: | |
| Training Data: Vaihingen | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 2.76 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_4x4_512x512_80k_vaihingen/fcn_hr18_4x4_512x512_80k_vaihingen_20211231_231216-2ec3ae8a.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_4x4_512x512_80k_vaihingen/fcn_hr18_4x4_512x512_80k_vaihingen_20211231_231216.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_vaihingen-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Vaihingen | |
| Metrics: | |
| mIoU: 72.5 | |
| mIoU(ms+flip): 73.52 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_vaihingen-512x512.py | |
| Metadata: | |
| Training Data: Vaihingen | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_4x4_512x512_80k_vaihingen/fcn_hr48_4x4_512x512_80k_vaihingen_20211231_231244-7133cb22.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_4x4_512x512_80k_vaihingen/fcn_hr48_4x4_512x512_80k_vaihingen_20211231_231244.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18s_4xb4-80k_isaid-896x896 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: iSAID | |
| Metrics: | |
| mIoU: 62.3 | |
| mIoU(ms+flip): 62.97 | |
| Config: configs/hrnet/fcn_hr18s_4xb4-80k_isaid-896x896.py | |
| Metadata: | |
| Training Data: iSAID | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18-Small | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 4.95 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_4x4_896x896_80k_isaid/fcn_hr18s_4x4_896x896_80k_isaid_20220118_001603-3cc0769b.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_4x4_896x896_80k_isaid/fcn_hr18s_4x4_896x896_80k_isaid_20220118_001603.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr18_4xb4-80k_isaid-896x896 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: iSAID | |
| Metrics: | |
| mIoU: 65.06 | |
| mIoU(ms+flip): 65.6 | |
| Config: configs/hrnet/fcn_hr18_4xb4-80k_isaid-896x896.py | |
| Metadata: | |
| Training Data: iSAID | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W18 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 8.3 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_4x4_896x896_80k_isaid/fcn_hr18_4x4_896x896_80k_isaid_20220110_182230-49bf752e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_4x4_896x896_80k_isaid/fcn_hr18_4x4_896x896_80k_isaid_20220110_182230.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |
| - Name: fcn_hr48_4xb4-80k_isaid-896x896 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: iSAID | |
| Metrics: | |
| mIoU: 67.8 | |
| mIoU(ms+flip): 68.53 | |
| Config: configs/hrnet/fcn_hr48_4xb4-80k_isaid-896x896.py | |
| Metadata: | |
| Training Data: iSAID | |
| Batch Size: 16 | |
| Architecture: | |
| - HRNetV2p-W48 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 16.89 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_4x4_896x896_80k_isaid/fcn_hr48_4x4_896x896_80k_isaid_20220114_174643-547fc420.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_4x4_896x896_80k_isaid/fcn_hr48_4x4_896x896_80k_isaid_20220114_174643.log.json | |
| Paper: | |
| Title: Deep High-Resolution Representation Learning for Human Pose Estimation | |
| URL: https://arxiv.org/abs/1908.07919 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218 | |
| Framework: PyTorch | |