Instance Segmentation on COCO (AP Mask, Delta)
46AP MaskMONA
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| MONABackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=4.16 M, Trainable backbone parameters %=4.67%, Extra Structure=true2024.08 | 46 | 0.9 | |
| FULLBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=89.14 M, Trainable backbone parameters %=100.00%, Extra Structure=false2024.08 | 45.1 | — | |
| ADAPTERBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=3.19 M, Trainable backbone parameters %=3.58%, Extra Structure=true2024.08 | 45 | -0.1 | |
| LORANDBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=4.68 M, Trainable backbone parameters %=5.23%, Extra Structure=true2024.08 | 44.7 | -0.4 | |
| ADAPTFORMERBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=1.60 M, Trainable backbone parameters %=1.79%, Extra Structure=true2024.08 | 44.6 | -0.5 | |
| LORABackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=3.06 M, Trainable backbone parameters %=3.43%, Extra Structure=true2024.08 | 43.9 | -1.2 | |
| PARTIAL-1Backbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=12.95 M, Trainable backbone parameters %=14.53%, Extra Structure=false2024.08 | 43.7 | -1.4 | |
| BITFITBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=0.21 M, Trainable backbone parameters %=0.23%, Extra Structure=false2024.08 | 43.6 | -1.5 | |
| NORMTUNINGBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=0.06 M, Trainable backbone parameters %=0.07%, Extra Structure=false2024.08 | 43.5 | -1.6 | |
| FIXEDBackbone=Swin-B (89M), Framework=Cascade Mask R-CNN, Trained Params=0.00 M, Trainable backbone parameters %=0.00%, Extra Structure=false2024.08 | 41.6 | -3.5 | |
| ConvNeXt-T + FDConvBackbone=ConvNeXt-T, Detector=Mask R-CNN, Params=51M, FLOPS=263G, Training Schedule=1x2025.03 | 40.8 | — | |
| ConvNeXt-T + KWBackbone=ConvNeXt-T, Detector=Mask R-CNN, Params=52M, FLOPS=262G, Training Schedule=1x2025.03 | 40.6 | — | |
| Swin-T + FDConvBackbone=Swin-T, Detector=Mask R-CNN, Params=51M, FLOPS=268G, Training Schedule=1x2025.03 | 40.5 | — | |
| ConvNeXt-TBackbone=ConvNeXt-T, Detector=Mask R-CNN, Params=48M, FLOPS=262G, Training Schedule=1x2025.03 | 39.7 | — | |
| Swin-TBackbone=Swin-T, Detector=Mask R-CNN, Params=48M, FLOPS=267G, Training Schedule=1x2025.03 | 39.3 | — |