| Models: | |
| - Name: mask_rcnn_convnext-t_p4_w7_fpn_fp16_ms-crop_3x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/convnext/mask_rcnn_convnext-t_p4_w7_fpn_fp16_ms-crop_3x_coco.py | |
| Metadata: | |
| Training Memory (GB): 7.3 | |
| Epochs: 36 | |
| Training Data: COCO | |
| Training Techniques: | |
| - AdamW | |
| - Mixed Precision Training | |
| Training Resources: 8x A100 GPUs | |
| Architecture: | |
| - ConvNeXt | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 46.2 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 41.7 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/convnext/mask_rcnn_convnext-t_p4_w7_fpn_fp16_ms-crop_3x_coco/mask_rcnn_convnext-t_p4_w7_fpn_fp16_ms-crop_3x_coco_20220426_154953-050731f4.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/2201.03545 | |
| Title: 'A ConvNet for the 2020s' | |
| README: configs/convnext/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: cascade_mask_rcnn_convnext-t_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco | |
| In Collection: Cascade Mask R-CNN | |
| Config: configs/convnext/cascade_mask_rcnn_convnext-t_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco.py | |
| Metadata: | |
| Training Memory (GB): 9.0 | |
| Epochs: 36 | |
| Training Data: COCO | |
| Training Techniques: | |
| - AdamW | |
| - Mixed Precision Training | |
| Training Resources: 8x A100 GPUs | |
| Architecture: | |
| - ConvNeXt | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 50.3 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 43.6 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/convnext/cascade_mask_rcnn_convnext-t_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco/cascade_mask_rcnn_convnext-t_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco_20220509_204200-8f07c40b.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/2201.03545 | |
| Title: 'A ConvNet for the 2020s' | |
| README: configs/convnext/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465 | |
| Version: v2.25.0 | |
| - Name: cascade_mask_rcnn_convnext-s_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco | |
| In Collection: Cascade Mask R-CNN | |
| Config: configs/convnext/cascade_mask_rcnn_convnext-s_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco.py | |
| Metadata: | |
| Training Memory (GB): 12.3 | |
| Epochs: 36 | |
| Training Data: COCO | |
| Training Techniques: | |
| - AdamW | |
| - Mixed Precision Training | |
| Training Resources: 8x A100 GPUs | |
| Architecture: | |
| - ConvNeXt | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 51.8 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 44.8 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/convnext/cascade_mask_rcnn_convnext-s_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco/cascade_mask_rcnn_convnext-s_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco_20220510_201004-3d24f5a4.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/2201.03545 | |
| Title: 'A ConvNet for the 2020s' | |
| README: configs/convnext/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465 | |
| Version: v2.25.0 | |