| instance-segmentation-on-coco-minival | BoTNet 200 (Mask R-CNN, single scale, 72 epochs) | #68 | mask AP: 44.4 |
| instance-segmentation-on-coco-minival | BoTNet 152 (Mask R-CNN, single scale, 72 epochs) | #73 | mask AP: 43.7 |
| instance-segmentation-on-coco-minival | BoTNet 50 (72 epochs) | #86 | mask AP: 40.7 |
| image-classification-on-imagenet | BoTNet T7 | #314 | Top 1 Accuracy: 84.7%Number of params: 75.1M |
| image-classification-on-imagenet | BoTNet T7-320 | #361 | Top 1 Accuracy: 84.2% |
| image-classification-on-imagenet | BoTNet T6 | #392 | Top 1 Accuracy: 84%Number of params: 53.9M |
| image-classification-on-imagenet | SENet-350 | #413 | Top 1 Accuracy: 83.8% |
| image-classification-on-imagenet | BoTNet T5 | #450 | Top 1 Accuracy: 83.5%GFLOPs: 19.3 |
| image-classification-on-imagenet | BoTNet T4 | #525 | Top 1 Accuracy: 82.8%Number of params: 54.7MGFLOPs: 10.9 |
| image-classification-on-imagenet | SENet-152 | #595 | Top 1 Accuracy: 82.2%Number of params: 66.6M |
| image-classification-on-imagenet | BoTNet T3 | #649 | Top 1 Accuracy: 81.7%Number of params: 33.5MGFLOPs: 7.3 |
| image-classification-on-imagenet | SENet-101 | #678 | Top 1 Accuracy: 81.4%Number of params: 49.2M |
| image-classification-on-imagenet | ResNet-101 | #761 | Top 1 Accuracy: 80%Number of params: 44.4M |
| image-classification-on-imagenet | SENet-50 | #795 | Top 1 Accuracy: 79.4%Number of params: 28.02M |
| image-classification-on-imagenet | ResNet-50 | #842 | Top 1 Accuracy: 78.8%Number of params: 25.5M |
| object-detection-on-coco-val2017 | BoTNet 152 (Mask R-CNN, single scale, 72 epochs) | – | box AP: 49.5AP50: 71AP75: 54.2 |
| object-detection-on-coco-val2017 | BoTNet 200 (Mask R-CNN, single scale, 72 epochs) | – | box AP: 49.7AP50: 71.3AP75: 54.6 |
| object-detection-on-coco-val2017 | BoTNet 50 (72 epochs) | – | box AP: 45.9 |