| Collections: | |
| - Name: DeepLabV3 | |
| License: Apache License 2.0 | |
| Metadata: | |
| Training Data: | |
| - Cityscapes | |
| - ADE20K | |
| - Pascal VOC 2012 + Aug | |
| - Pascal Context | |
| - Pascal Context 59 | |
| - COCO-Stuff 10k | |
| - COCO-Stuff 164k | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| README: configs/deeplabv3/README.md | |
| Frameworks: | |
| - PyTorch | |
| Models: | |
| - Name: deeplabv3_r50-d8_4xb2-40k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.09 | |
| mIoU(ms+flip): 80.45 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.1 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes/deeplabv3_r50-d8_512x1024_40k_cityscapes_20200605_022449-acadc2f8.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes/deeplabv3_r50-d8_512x1024_40k_cityscapes_20200605_022449.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb2-40k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.12 | |
| mIoU(ms+flip): 79.61 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_40k_cityscapes/deeplabv3_r101-d8_512x1024_40k_cityscapes_20200605_012241-7fd3f799.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_40k_cityscapes/deeplabv3_r101-d8_512x1024_40k_cityscapes_20200605_012241.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb2-40k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.58 | |
| mIoU(ms+flip): 79.89 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb2-40k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_40k_cityscapes/deeplabv3_r50-d8_769x769_40k_cityscapes_20200606_113723-7eda553c.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_40k_cityscapes/deeplabv3_r50-d8_769x769_40k_cityscapes_20200606_113723.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb2-40k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.27 | |
| mIoU(ms+flip): 80.11 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb2-40k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 10.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_40k_cityscapes/deeplabv3_r101-d8_769x769_40k_cityscapes_20200606_113809-c64f889f.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_40k_cityscapes/deeplabv3_r101-d8_769x769_40k_cityscapes_20200606_113809.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r18-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.7 | |
| mIoU(ms+flip): 78.27 | |
| Config: configs/deeplabv3/deeplabv3_r18-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-18-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.7 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes/deeplabv3_r18-d8_512x1024_80k_cityscapes_20201225_021506-23dffbe2.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes/deeplabv3_r18-d8_512x1024_80k_cityscapes-20201225_021506.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.32 | |
| mIoU(ms+flip): 80.57 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes/deeplabv3_r50-d8_512x1024_80k_cityscapes_20200606_113404-b92cfdd4.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes/deeplabv3_r50-d8_512x1024_80k_cityscapes_20200606_113404.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 80.2 | |
| mIoU(ms+flip): 81.21 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503-9e428899.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb2-amp-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 80.48 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| - (FP16) | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 5.75 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-774d9cec.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r18-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.6 | |
| mIoU(ms+flip): 78.26 | |
| Config: configs/deeplabv3/deeplabv3_r18-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-18-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes/deeplabv3_r18-d8_769x769_80k_cityscapes_20201225_021506-6452126a.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes/deeplabv3_r18-d8_769x769_80k_cityscapes-20201225_021506.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.89 | |
| mIoU(ms+flip): 81.06 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes/deeplabv3_r50-d8_769x769_80k_cityscapes_20200606_221338-788d6228.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes/deeplabv3_r50-d8_769x769_80k_cityscapes_20200606_221338.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.67 | |
| mIoU(ms+flip): 80.81 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes/deeplabv3_r101-d8_769x769_80k_cityscapes_20200607_013353-60e95418.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes/deeplabv3_r101-d8_769x769_80k_cityscapes_20200607_013353.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d16-mg124_4xb2-40k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.71 | |
| mIoU(ms+flip): 78.63 | |
| Config: configs/deeplabv3/deeplabv3_r101-d16-mg124_4xb2-40k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D16-MG124 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 4.7 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes/deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes_20200908_005644-67b0c992.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes/deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes-20200908_005644.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d16-mg124_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.36 | |
| mIoU(ms+flip): 79.84 | |
| Config: configs/deeplabv3/deeplabv3_r101-d16-mg124_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101-D16-MG124 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes/deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes_20200908_005644-57bb8425.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes/deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes-20200908_005644.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r18b-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.26 | |
| mIoU(ms+flip): 77.88 | |
| Config: configs/deeplabv3/deeplabv3_r18b-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-18b-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18b-d8_512x1024_80k_cityscapes/deeplabv3_r18b-d8_512x1024_80k_cityscapes_20201225_094144-46040cef.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18b-d8_512x1024_80k_cityscapes/deeplabv3_r18b-d8_512x1024_80k_cityscapes-20201225_094144.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50b-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.63 | |
| mIoU(ms+flip): 80.98 | |
| Config: configs/deeplabv3/deeplabv3_r50b-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50b-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.0 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50b-d8_512x1024_80k_cityscapes/deeplabv3_r50b-d8_512x1024_80k_cityscapes_20201225_155148-ec368954.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50b-d8_512x1024_80k_cityscapes/deeplabv3_r50b-d8_512x1024_80k_cityscapes-20201225_155148.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101b-d8_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 80.01 | |
| mIoU(ms+flip): 81.21 | |
| Config: configs/deeplabv3/deeplabv3_r101b-d8_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101b-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101b-d8_512x1024_80k_cityscapes/deeplabv3_r101b-d8_512x1024_80k_cityscapes_20201226_171821-8fd49503.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101b-d8_512x1024_80k_cityscapes/deeplabv3_r101b-d8_512x1024_80k_cityscapes-20201226_171821.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r18b-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 75.63 | |
| mIoU(ms+flip): 77.51 | |
| Config: configs/deeplabv3/deeplabv3_r18b-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-18b-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 1.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18b-d8_769x769_80k_cityscapes/deeplabv3_r18b-d8_769x769_80k_cityscapes_20201225_094144-fdc985d9.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18b-d8_769x769_80k_cityscapes/deeplabv3_r18b-d8_769x769_80k_cityscapes-20201225_094144.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50b-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 78.8 | |
| mIoU(ms+flip): 80.27 | |
| Config: configs/deeplabv3/deeplabv3_r50b-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-50b-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50b-d8_769x769_80k_cityscapes/deeplabv3_r50b-d8_769x769_80k_cityscapes_20201225_155404-87fb0cf4.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50b-d8_769x769_80k_cityscapes/deeplabv3_r50b-d8_769x769_80k_cityscapes-20201225_155404.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101b-d8_4xb2-80k_cityscapes-769x769 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 79.41 | |
| mIoU(ms+flip): 80.73 | |
| Config: configs/deeplabv3/deeplabv3_r101b-d8_4xb2-80k_cityscapes-769x769.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - R-101b-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 10.7 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101b-d8_769x769_80k_cityscapes/deeplabv3_r101b-d8_769x769_80k_cityscapes_20201226_190843-9142ee57.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101b-d8_769x769_80k_cityscapes/deeplabv3_r101b-d8_769x769_80k_cityscapes-20201226_190843.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-80k_ade20k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 42.42 | |
| mIoU(ms+flip): 43.28 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 8.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_80k_ade20k/deeplabv3_r50-d8_512x512_80k_ade20k_20200614_185028-0bb3f844.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_80k_ade20k/deeplabv3_r50-d8_512x512_80k_ade20k_20200614_185028.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-80k_ade20k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 44.08 | |
| mIoU(ms+flip): 45.19 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 12.4 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_80k_ade20k/deeplabv3_r101-d8_512x512_80k_ade20k_20200615_021256-d89c7fa4.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_80k_ade20k/deeplabv3_r101-d8_512x512_80k_ade20k_20200615_021256.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-160k_ade20k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 42.66 | |
| mIoU(ms+flip): 44.09 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_160k_ade20k/deeplabv3_r50-d8_512x512_160k_ade20k_20200615_123227-5d0ee427.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_160k_ade20k/deeplabv3_r50-d8_512x512_160k_ade20k_20200615_123227.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-160k_ade20k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.0 | |
| mIoU(ms+flip): 46.66 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k/deeplabv3_r101-d8_512x512_160k_ade20k_20200615_105816-b1f72b3b.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k/deeplabv3_r101-d8_512x512_160k_ade20k_20200615_105816.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-20k_voc12aug-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 76.17 | |
| mIoU(ms+flip): 77.42 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.1 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_20k_voc12aug/deeplabv3_r50-d8_512x512_20k_voc12aug_20200617_010906-596905ef.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_20k_voc12aug/deeplabv3_r50-d8_512x512_20k_voc12aug_20200617_010906.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-20k_voc12aug-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 78.7 | |
| mIoU(ms+flip): 79.95 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-20k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_20k_voc12aug/deeplabv3_r101-d8_512x512_20k_voc12aug_20200617_010932-8d13832f.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_20k_voc12aug/deeplabv3_r101-d8_512x512_20k_voc12aug_20200617_010932.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-40k_voc12aug-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 77.68 | |
| mIoU(ms+flip): 78.78 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_40k_voc12aug/deeplabv3_r50-d8_512x512_40k_voc12aug_20200613_161546-2ae96e7e.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_40k_voc12aug/deeplabv3_r50-d8_512x512_40k_voc12aug_20200613_161546.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-40k_voc12aug-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal VOC 2012 + Aug | |
| Metrics: | |
| mIoU: 77.92 | |
| mIoU(ms+flip): 79.18 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_voc12aug-512x512.py | |
| Metadata: | |
| Training Data: Pascal VOC 2012 + Aug | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_40k_voc12aug/deeplabv3_r101-d8_512x512_40k_voc12aug_20200613_161432-0017d784.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_40k_voc12aug/deeplabv3_r101-d8_512x512_40k_voc12aug_20200613_161432.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-40k_pascal-context-480x480 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context | |
| Metrics: | |
| mIoU: 46.55 | |
| mIoU(ms+flip): 47.81 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_pascal-context-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context/deeplabv3_r101-d8_480x480_40k_pascal_context_20200911_204118-1aa27336.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context/deeplabv3_r101-d8_480x480_40k_pascal_context-20200911_204118.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-80k_pascal-context-480x480 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context | |
| Metrics: | |
| mIoU: 46.42 | |
| mIoU(ms+flip): 47.53 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_pascal-context-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context/deeplabv3_r101-d8_480x480_80k_pascal_context_20200911_170155-2a21fff3.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context/deeplabv3_r101-d8_480x480_80k_pascal_context-20200911_170155.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-40k_pascal-context-59-480x480 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context 59 | |
| Metrics: | |
| mIoU: 52.61 | |
| mIoU(ms+flip): 54.28 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_pascal-context-59-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context 59 | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context_59/deeplabv3_r101-d8_480x480_40k_pascal_context_59_20210416_110332-cb08ea46.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context_59/deeplabv3_r101-d8_480x480_40k_pascal_context_59-20210416_110332.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-80k_pascal-context-59-480x480 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Pascal Context 59 | |
| Metrics: | |
| mIoU: 52.46 | |
| mIoU(ms+flip): 54.09 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_pascal-context-59-480x480.py | |
| Metadata: | |
| Training Data: Pascal Context 59 | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context_59/deeplabv3_r101-d8_480x480_80k_pascal_context_59_20210416_113002-26303993.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context_59/deeplabv3_r101-d8_480x480_80k_pascal_context_59-20210416_113002.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-20k_coco-stuff10k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 10k | |
| Metrics: | |
| mIoU: 34.66 | |
| mIoU(ms+flip): 36.08 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-20k_coco-stuff10k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 10k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_20k_coco-stuff10k/deeplabv3_r50-d8_512x512_4x4_20k_coco-stuff10k_20210821_043025-b35f789d.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_20k_coco-stuff10k/deeplabv3_r50-d8_512x512_4x4_20k_coco-stuff10k_20210821_043025.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-20k_coco-stuff10k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 10k | |
| Metrics: | |
| mIoU: 37.3 | |
| mIoU(ms+flip): 38.42 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-20k_coco-stuff10k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 10k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 13.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_20k_coco-stuff10k/deeplabv3_r101-d8_512x512_4x4_20k_coco-stuff10k_20210821_043025-c49752cb.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_20k_coco-stuff10k/deeplabv3_r101-d8_512x512_4x4_20k_coco-stuff10k_20210821_043025.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-40k_coco-stuff10k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 10k | |
| Metrics: | |
| mIoU: 35.73 | |
| mIoU(ms+flip): 37.09 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-40k_coco-stuff10k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 10k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_40k_coco-stuff10k/deeplabv3_r50-d8_512x512_4x4_40k_coco-stuff10k_20210821_043305-dc76f3ff.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_40k_coco-stuff10k/deeplabv3_r50-d8_512x512_4x4_40k_coco-stuff10k_20210821_043305.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-40k_coco-stuff10k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 10k | |
| Metrics: | |
| mIoU: 37.81 | |
| mIoU(ms+flip): 38.8 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_coco-stuff10k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 10k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_40k_coco-stuff10k/deeplabv3_r101-d8_512x512_4x4_40k_coco-stuff10k_20210821_043305-636cb433.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_40k_coco-stuff10k/deeplabv3_r101-d8_512x512_4x4_40k_coco-stuff10k_20210821_043305.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-80k_coco-stuff164k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 39.38 | |
| mIoU(ms+flip): 40.03 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-80k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_80k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_80k_coco-stuff164k_20210709_163016-88675c24.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_80k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_80k_coco-stuff164k_20210709_163016.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-80k_coco-stuff164k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 40.87 | |
| mIoU(ms+flip): 41.5 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 13.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_80k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_80k_coco-stuff164k_20210709_201252-13600dc2.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_80k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_80k_coco-stuff164k_20210709_201252.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 41.09 | |
| mIoU(ms+flip): 41.69 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_160k_coco-stuff164k_20210709_163016-49f2812b.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_160k_coco-stuff164k_20210709_163016.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 41.82 | |
| mIoU(ms+flip): 42.49 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k_20210709_155402-f035acfd.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k_20210709_155402.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r50-d8_4xb4-320k_coco-stuff164k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 41.37 | |
| mIoU(ms+flip): 42.22 | |
| Config: configs/deeplabv3/deeplabv3_r50-d8_4xb4-320k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k_20210709_155403-51b21115.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k_20210709_155403.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |
| - Name: deeplabv3_r101-d8_4xb4-320k_coco-stuff164k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 42.61 | |
| mIoU(ms+flip): 43.42 | |
| Config: configs/deeplabv3/deeplabv3_r101-d8_4xb4-320k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k_20210709_155402-3cbca14d.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k_20210709_155402.log.json | |
| Paper: | |
| Title: Rethinking atrous convolution for semantic image segmentation | |
| URL: https://arxiv.org/abs/1706.05587 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/aspp_head.py#L54 | |
| Framework: PyTorch | |