Image Restoration Models
Test-time Local Converter
Introduced by Chu et al. in Improving Image Restoration by Revisiting Global Information AggregationTLC convert the global operation to a local one so that it extract representations based on local spatial region of features as in training phase.
Source: Improving Image Restoration by Revisiting Global Information Aggregation
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Class Incremental Learning | 1 | 5.26% |
| Continual Learning | 1 | 5.26% |
| Incremental Learning | 1 | 5.26% |
| Feature Engineering | 1 | 5.26% |
| Symbolic Regression | 1 | 5.26% |
| Management | 1 | 5.26% |
| Novel View Synthesis | 1 | 5.26% |
| Image Captioning | 1 | 5.26% |
| Language Modelling | 1 | 5.26% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
