Loss Functions
Lovasz-Softmax
The Lovasz-Softmax loss is a loss function for multiclass semantic segmentation that incorporates the softmax operation in the Lovasz extension. The Lovasz extension is a means by which we can achieve direct optimization of the mean intersection-over-union loss in neural networks.
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Semantic Segmentation | 4 | 30.77% |
| Image Segmentation | 2 | 15.38% |
| 3D Semantic Segmentation | 2 | 15.38% |
| Autonomous Driving | 2 | 15.38% |
| Medical Image Segmentation | 1 | 7.69% |
| Scene Understanding | 1 | 7.69% |
| Robust 3D Semantic Segmentation | 1 | 7.69% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
