Instance Segmentation on Poplar-Leaf (test)
70mAPLeafInst
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| LeafInstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 70 | 91.9 | 77 | |
| SoloV2Backbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 64.9 | 88.6 | 71.7 | |
| PointRendBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 63.6 | 85 | 70.5 | |
| MaskDinoBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 63.5 | 85.7 | 68.9 | |
| YOLOV11Backbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 62.9 | 89.3 | — | |
| CascadeRcnnBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 62.3 | 83 | 69.3 | |
| MaskRcnnBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 62.1 | 90.7 | 68.8 | |
| YOLOV8Backbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 62 | 89.7 | — | |
| QueryinstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 58.2 | 79.7 | 64.4 | |
| Mask2formerBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 58 | 78.6 | 53.4 | |
| SoloBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 57.9 | 84.3 | 65.1 | |
| BoxInstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 57.9 | 87.9 | 64.9 | |
| YOLACTBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 50.3 | 78.6 | 53.4 | |
| SparseInstBackbone=ResNet-50, Pre-trained=ImageNet [65], Resolution=1024 x 1024, Training epochs=36, Optimizer=SGD, Initial learning rate=0.005, Batch size=42026.03 | 43.5 | 68.9 | 45.5 |