Loss Functions
Object-Aware Loss
Introduced by Lee et al. in Object-Aware Domain Generalization for Object DetectionOA-Loss reduces the domain gap between the original and augmented images. OA-Loss enables the model to learn semantic relations of foreground and background instances from multi-domain.
Source: Object-Aware Domain Generalization for Object Detection
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Autonomous Driving | 1 | 20.00% |
| Domain Generalization | 1 | 20.00% |
| Object Detection | 1 | 20.00% |
| Object Localization | 1 | 20.00% |
| Robust Object Detection | 1 | 20.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
