| image-classification-on-imagenet | LIP-ResNet-101 | #722 | Top 1 Accuracy: 79.33%Number of params: 42.9M |
| image-classification-on-imagenet | ResNet-50 (LIP Bottleneck-256) | #799 | Top 1 Accuracy: 78.15%Number of params: 25.8M |
| image-classification-on-imagenet | LIP-DenseNet-BC-121 | #851 | Top 1 Accuracy: 76.64%Number of params: 8.7M |
| object-detection-on-coco | Faster R-CNN (LIP-ResNet-101-MD w FPN) | #150 | box mAP: 43.9AP50: 65.7AP75: 48.1APS: 25.4APM: 46.7APL: 56.3 |
| object-detection-on-coco-minival | Faster R-CNN (LIP-ResNet-101) | #161 | box AP: 41.7AP50: 63.6AP75: 45.6APS: 25.2APM: 45.8 |