Loss Functions
Generalized Focal Loss
Introduced by Li et al. in Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object DetectionGeneralized Focal Loss (GFL) is a loss function for object detection that combines Quality Focal Loss and Distribution Focal Loss into a general form.
Source: Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Multi-Task Learning | 1 | 16.67% |
| Classification | 1 | 16.67% |
| Object | 1 | 16.67% |
| Dense Object Detection | 1 | 16.67% |
| General Classification | 1 | 16.67% |
| Object Detection | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
