# Benchmark and Model Zoo

## CNN-based (w/ ImageNet-1k pretrained)
### Faster R-CNN 
| Backbone | Lr Schd | box mAP (minival) |  #params | FLOPs | config | log | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | 
| DB-ResNet50 | 1x |  40.8 | 69M | 284G | [config](configs/cbnet/faster_rcnn_cbv2d1_r50_fpn_1x_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/faster_rcnn_cbv2d1_r50_fpn_1x_coco.log.json)| [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/faster_rcnn_cbv2d1_r50_fpn_1x_coco.pth.zip)| 


### Cascade R-CNN (1600x1400)
| Backbone | Lr Schd | box mAP (minival/test-dev)|  #params | FLOPs | config | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | 
| DB-Res2Net101-DCN | 20e |  53.7/- | 141M | 429G | [config](configs/cbnet/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_coco.pth.zip)| 
| DB-Res2Net101-DCN |  20e + 1x (swa) | 54.8/55.3 | 141M | 429G | [config (test only)](configs/cbnet/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_coco_swa.pth.zip) | 

### Cascade R-CNN w/ 4conv1fc (1600x1400)
| Backbone | Lr Schd | box mAP (minival/test-dev)|  #params | FLOPs | config | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | 
| DB-Res2Net101-DCN | 20e |  54.1/- | 146M | 774G | [config](configs/cbnet/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_giou_4conv1f_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_giou_4conv1f_coco.pth.zip)| 
| DB-Res2Net101-DCN |  20e + 1x (swa) | 55.3/55.6 | 146M | 774G | [config (test only)](configs/cbnet/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_giou_4conv1f_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_rcnn_cbv2d1_r2_101_mdconv_fpn_20e_fp16_ms400-1400_giou_4conv1f_coco_swa.pth.zip) | 


**Notes**: 
- For SWA training, please refer to [SWA Object Detection](https://github.com/hyz-xmaster/swa_object_detection)

## Transformer-based (w/ ImageNet-1k pretrained)

### Mask R-CNN

| Backbone |  Lr Schd | box mAP (minival) | mask mAP (minival) | #params | FLOPs | config | log | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | 
| DB-Swin-T |  3x | 50.2 | 44.5 | 76M | 357G | [config](configs/cbnet/mask_rcnn_cbv2_swin_small_patch4_window7_mstrain_480-800_adamw_3x_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/mask_rcnn_cbv2_swin_tiny_patch4_window7_mstrain_480-800_adamw_3x_coco.log.json)  | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/mask_rcnn_cbv2_swin_tiny_patch4_window7_mstrain_480-800_adamw_3x_coco.pth.zip) |


### Cascade Mask R-CNN w/ 4conv1fc
| Backbone |  Lr Schd | box mAP (minival)| mask mAP (minival)| #params | FLOPs | config | log | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| DB-Swin-T |  3x | 53.6 | 46.2 | 114M | 836G | [config](configs/cbnet/cascade_mask_rcnn_cbv2_swin_tiny_patch4_window7_mstrain_480-800_adamw_3x_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_mask_rcnn_cbv2_swin_tiny_patch4_window7_mstrain_480-800_adamw_3x_coco.log.json) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_mask_rcnn_cbv2_swin_tiny_patch4_window7_mstrain_480-800_adamw_3x_coco.pth.zip) | 

### Cascade Mask R-CNN w/ 4conv1fc (1600x1400)
| Backbone | Lr Schd | box mAP (minival/test-dev)| mask mAP (minival/test-dev)| #params | FLOPs | config | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| DB-Swin-S | 3x | 56.3/56.9 | 48.6/49.1 | 156M | 1016G | [config](configs/cbnet/cascade_mask_rcnn_cbv2_swin_small_patch4_window7_mstrain_400-1400_adamw_3x_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/cascade_mask_rcnn_cbv2_swin_small_patch4_window7_mstrain_400-1400_adamw_3x_coco.pth.zip)| 

## Transformer-based (w/ ImageNet-22k pretrained)
### HTC (1600x1400)
| Backbone | Lr Schd | box mAP (minival/test-dev) | mask mAP (minival/test-dev) | #params | FLOPs | config | model |
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| DB-Swin-B | 20e | 57.9/- | 50.2/- | 231M | 1004G | [config](configs/cbnet/htc_cbv2_swin_base_patch4_window7_mstrain_400-1400_adamw_20e_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/htc_cbv2_swin_base22k_patch4_window7_mstrain_400-1400_adamw_20e_coco.pth.zip) |
| DB-Swin-B | 20e + 1x (swa) | 58.2/58.6 | 50.4/51.1 | 231M | 1004G | [config (test only)](configs/cbnet/htc_cbv2_swin_base_patch4_window7_mstrain_400-1400_adamw_20e_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/htc_cbv2_swin_base22k_patch4_window7_mstrain_400-1400_adamw_20e_coco_swa.pth.zip)| 

### HTC (bbox head w/ 4conv1fc) (1600x1400)
*Compared to regular HTC, our HTC uses 4conv1fc in bbox head.*
| Backbone | Lr Schd | box mAP (minival/test-dev) | mask mAP (minival/test-dev) | #params | FLOPs | config | model |
| :---: |:---: | :---: | :---: | :---: | :---: | :---: | :---: |
| DB-Swin-B | 20e | 58.4/58.7 | 50.7/51.1 | 235M | 1348G | [config](configs/cbnet/htc_cbv2_swin_base_patch4_window7_mstrain_400-1400_giou_4conv1f_adamw_20e_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/htc_cbv2_swin_base22k_patch4_window7_mstrain_400-1400_giou_4conv1f_adamw_20e_coco.pth.zip) |
| DB-Swin-L | 1x | 59.1/59.4 | 51.0/51.6 | 453M | 2162G | [config](configs/cbnet/htc_cbv2_swin_large_patch4_window7_mstrain_400-1400_giou_4conv1f_adamw_1x_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/htc_cbv2_swin_large22k_patch4_window7_mstrain_400-1400_giou_4conv1f_adamw_1x_coco.pth.zip) |
| DB-Swin-L (TTA) |  1x | 59.6/60.1 | 51.8/52.3 | 453M | - | [config](configs/cbnet/htc_cbv2_swin_large_patch4_window7_mstrain_400-1400_giou_4conv1f_adamw_1x_coco.py) | [github](https://github.com/CBNetwork/storage/releases/download/v1.0.0/htc_cbv2_swin_large22k_patch4_window7_mstrain_400-1400_giou_4conv1f_adamw_1x_coco.pth.zip) |

TTA denotes test time augmentation.
 
**Notes**: 

- **Pre-trained models of Swin Transformer can be downloaded from [Swin Transformer for ImageNet Classification](https://github.com/microsoft/Swin-Transformer)**.