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- # Strong Baselines
-
- We train Mask R-CNN with large-scale jittor and longer schedule as strong baselines.
- The modifications follow those in [Detectron2](https://github.com/facebookresearch/detectron2/tree/master/configs/new_baselines).
-
- ## Results and models
-
- | Backbone | Style | Lr schd | Mem (GB) | Inf time (fps) | box AP | mask AP | Config | Download |
- | :-------------: | :-----: | :-----: | :------: | :------------: | :----: | :-----: | :------: | :--------: |
- | R-50-FPN | pytorch | 50e | | | | | [config](./mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_50e_coco.py) | [model]() | [log]() |
- | R-50-FPN | pytorch | 100e | | | | | [config](./mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py) | [model]() | [log]() |
- | R-50-FPN | caffe | 100e | | | 44.7 | 40.4 | [config](./mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py) | [model]() | [log]() |
- | R-50-FPN | caffe | 400e | | | | | [config](./mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_400e_coco.py) | [model]() | [log]() |
-
- ## Notice
-
- When using large-scale jittering, there are sometimes empty proposals in the box and mask heads during training.
- This requires MMSyncBN that allows empty tensors. Therefore, please use mmcv-full>=1.3.14 to train models supported in this directory.
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