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- Models:
- - Name: mask-rcnn_swin-s-p4-w7_fpn_amp-ms-crop-3x_coco
- In Collection: Mask R-CNN
- Config: configs/swin/mask-rcnn_swin-s-p4-w7_fpn_amp-ms-crop-3x_coco.py
- Metadata:
- Training Memory (GB): 11.9
- Epochs: 36
- Training Data: COCO
- Training Techniques:
- - AdamW
- Training Resources: 8x V100 GPUs
- Architecture:
- - Swin Transformer
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 48.2
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 43.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco/mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco_20210903_104808-b92c91f1.pth
- Paper:
- URL: https://arxiv.org/abs/2107.08430
- Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
- README: configs/swin/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
- Version: v2.16.0
- - Name: mask-rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco
- In Collection: Mask R-CNN
- Config: configs/swin/mask-rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco.py
- Metadata:
- Training Memory (GB): 10.2
- Epochs: 36
- Training Data: COCO
- Training Techniques:
- - AdamW
- Training Resources: 8x V100 GPUs
- Architecture:
- - Swin Transformer
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 46.0
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 41.6
- Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco/mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco_20210906_131725-bacf6f7b.pth
- Paper:
- URL: https://arxiv.org/abs/2107.08430
- Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
- README: configs/swin/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
- Version: v2.16.0
- - Name: mask-rcnn_swin-t-p4-w7_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/swin/mask-rcnn_swin-t-p4-w7_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 7.6
- Epochs: 12
- Training Data: COCO
- Training Techniques:
- - AdamW
- Training Resources: 8x V100 GPUs
- Architecture:
- - Swin Transformer
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.7
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 39.3
- Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-t-p4-w7_fpn_1x_coco/mask_rcnn_swin-t-p4-w7_fpn_1x_coco_20210902_120937-9d6b7cfa.pth
- Paper:
- URL: https://arxiv.org/abs/2107.08430
- Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
- README: configs/swin/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
- Version: v2.16.0
- - Name: mask-rcnn_swin-t-p4-w7_fpn_amp-ms-crop-3x_coco
- In Collection: Mask R-CNN
- Config: configs/swin/mask-rcnn_swin-t-p4-w7_fpn_amp-ms-crop-3x_coco.py
- Metadata:
- Training Memory (GB): 7.8
- Epochs: 36
- Training Data: COCO
- Training Techniques:
- - AdamW
- Training Resources: 8x V100 GPUs
- Architecture:
- - Swin Transformer
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 46.0
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 41.7
- Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco/mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco_20210908_165006-90a4008c.pth
- Paper:
- URL: https://arxiv.org/abs/2107.08430
- Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
- README: configs/swin/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
- Version: v2.16.0
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